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A step toward evolving biped walking behavior through indirect encodingOlson, Randal S. 01 January 2010 (has links)
Teaching simulated biped robots to walk is a popular problem in machine learning. However, until this thesis, evolving a biped controller has not been attempted through an indirect encoding, i.e. a compressed representation of the solution, despite the fact that natural bipeds such as humans evolved through such an indirect encoding (i.e. DNA). Thus the promise for indirect encoding is to evolve gaits that rival those seen in nature. In this thesis, an indirect encoding called HyperNEAT evolves a controller for a biped robot in a computer simulation. To most effectively explore the deceptive behavior space of biped walkers, novelty search is applied as a fitness metric. The result is that although the indirect encoding can evolve a stable bipedal gait, the overall neural architecture is brittle to small mutations. This result suggests that some capabilities might be necessary to include beyond indirect encoding, such as lifetime adaptation. Thus this thesis provides fresh insight into the requisite ingredients for the eventual achievement of fluid bipedal walking through artificial evolution.
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Network engineering using multi-objective evolutionary algorithmsBaruani, Atumbe Jules 12 1900 (has links)
Thesis (MSc)--University of Stellenbosch, 2007. / ENGLISH ABSTRACT: We use Evolutionary Multi-Objective Optimisation (EMOO) algorithms to optimise objective
functions that reflect situations in communication networks. These include functions
that optimise Network Engineering (NE) objective functions in core, metro and wireless
sensor networks. The main contributions of this thesis are threefold.
Routing and Wavelength Assignment (RWA) for IP backbone networks.
Routing and Wavelength Assignment (RWA) is a problem that has been widely addressed
by the optical research community. A recent interest in this problem has been raised by the
need to achieve routing optimisation in the emerging generation multilayer networks where
data networks are layered above a Dense Wavelength Division Multiplexing (DWDM) network.
We formulate the RWA as both a single and a multi-objective optimisation problem
which are solved using a two-step solution where (1) a set of paths are found using genetic
optimisation and (2) a graph coloring approach is implemented to assign wavelengths to
these paths. The experimental results from both optimisation scenarios reveal the impact
of (1) the cost metric used which equivalently defines the fitness function (2) the algorithmic
solution adopted and (3) the topology of the network on the performance achieved by
the RWA procedure in terms of path quality and wavelength assignment.
Optimisation of Arrayed Waveguide Grating (AWG) Metro Networks.
An Arrayed Waveguide Grating (AWG) is a device that can be used as a multiplexer or
demultiplexer in WDM systems. It can also be used as a drop-and-insert element or even
a wavelength router. We take a closer look at how the hardware and software parameters
of an AWG can be fine tuned in order to maximise throughput and minimise the delay.
We adopt a multi-objective optimisation approach for multi-service AWG-based single hop metro WDM networks. Using a previously proposed multi-objective optimisation model
as a benchmark, we propose several EMOO solutions and compare their efficiency by
evaluating their impact on the performance achieved by the AWG optimisation process.
Simulation reveals that (1) different EMOO algorithms can exhibit different performance
patterns and (2) good network planning and operation solutions for a wide range of traffic
scenarios can result from a well selected EMOO algorithm.
Wireless Sensor Networks (WSNs) Topology (layout) Optimisation.
WSNs have been used in a number of application areas to achieve vital functions in situations
where humans cannot constantly be available for certain tasks such as in hostile areas
like war zones, seismic sensing where continuous inspection and detection are needed, and
many other applications such as environment monitoring, military operations and surveillance.
Research and practice have shown that there is a need to optimise the topology
(layout) of such sensors on the ground because the position on which they land may affect
the sensing efficiency. We formulate the problem of layout optimisation as a multi-objective
optimisation problem consisting of maximising both the coverage (area) and the lifetime of
the wireless sensor network. We propose different algorithmic evolutionary multi-objective
methods and compare their performance in terms of Pareto solutions. Simulations reveal
that the Pareto solutions found lead to different performance patterns and types of layouts. / AFRIKAANSE OPSOMMING: Ons gebruik ”Evolutionary Multi-Objective Optimisation (EMOO)” algoritmes om teiken
funksies, wat egte situasies in kommunikasie netwerke voorstel, te optimiseer. Hierdie sluit
funksies in wat ”Network Engineering” teiken funksies in kern, metro en wireless sensor
netwerke optimiseer. Die hoof doelwitte van hierdie tesis is dus drievuldig.
RWA vir IP backbone netwerke
”Routing and Wavelength Assignment (RWA)” is ’n probleem wat al menigte kere in
die optiese navorsings kringe aangespreek is. Belangstelling in hierdie veld het onlangs
ontstaan a.g.v. die aanvraag na die optimisering van routering in die opkomende generasie
van veelvuldige vlak netwerke waar data netwerke in ’n vlak ho¨er as ’n ”Dense Wavelength
Division Multiplexing (DWDM)” netwerk gele is. Ons formuleer die RWA as beide ’n enkele
and veelvuldige teiken optimiserings probleem wat opgelos word deur ’n 2-stap oplossing
waar (1) ’n stel roetes gevind word deur genetiese optimisering te gebruik en (2) ’n grafiek
kleuring benadering geimplementeer word om golflengtes aan hierdie roetes toe te ken.
Die eksperimentele resultate van beide optimiserings gevalle vertoon die impak van (1) die
koste on wat gebruik word wat die ekwalente fitness funksie definieer , (2) die algoritmiese
oplossing wat gebruik word en (3) die topologie van die netwerk op die werkverrigting van
die RWA prosedure i.t.v. roete kwaliteit en golflengte toekenning.
Optimisering van AWG Metro netwerk
’n ”Arrayed Waveguide Grating (AWG)” is ’n toestel wat gebruik kan word as ’n multipleksor
of demultipleksor in WDM sisteme. Dit kan ook gebruik word as ’n val-en-inplaas
element of selfs ’n golflengte router. Kennis word ingestel na hoe die hardeware en sagteware
parameters van ’n AWG ingestel kan word om die deurset tempo te maksimeer en vertragings te minimiseer. Ons neem ’n multi-teiken optimiserings benadering vir multi diens,
AWG gebaseerde, enkel skakel, metro WDM netwerke aan. Deur ’n vooraf voorgestelde
multi teiken optimiserings model as ”benchmark” te gebruik, stel ons ’n aantal EMOO
oplossings voor en vergelyk ons hul effektiwiteit deur hul impak op die werkverrigting wat
deur die AWG optimiserings proses bereik kan word, te vergelyk. Simulasie modelle wys
dat (1) verskillende EMOO algoritmes verskillende werkverrigtings patrone kan vertoon
en (2) dat goeie netwerk beplanning en werking oplossings vir ’n wye verskeidenheid van
verkeer gevalle kan plaasvind a.g.v ’n EMOO algoritme wat reg gekies word.
”Wireless Sensor Network” Topologie Optimisering
WSNs is al gebruik om belangrike funksies te verrig in ’n aantal toepassings waar menslike
beheer nie konstant beskikbaar is nie, of kan wees nie. Voorbeelde van sulke gevalle is oorlog
gebiede, seismiese metings waar aaneenlopende inspeksie en meting nodig is, omgewings
meting, militˆere operasies en bewaking. Navorsing en praktiese toepassing het getoon dat
daar ’n aanvraag na die optimisering van die topologie van sulke sensors is, gebaseer op
gronde van die feit dat die posisie waar die sensor beland, die effektiwiteit van die sensor
kan affekteer. Ons formuleer die probleem van uitleg optimisering as ’n veelvuldige
vlak optimiserings probleem wat bestaan uit die maksimering van beide die bedekkings
area en die leeftyd van die wireless sensor netwerk. Ons stel verskillende algoritmiese,
evolutionˆere, veelvuldige vlak oplossings voor en vergelyk hul werkverrigting i.t.v Pareto
oplossings. Simulasie modelle wys dat die Pareto oplossings wat gevind word lei na verskillende
werkverrigtings patrone en uitleg tipes.
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Real time optimal water allocation in the Orange River catchment in South AfricaOlofintoye, Oluwatosin Onaopemipo January 2015 (has links)
Submitted in fulfillment of the requirements of the degree of Doctor of Engineering: Civil Engineering, Durban University of Technology. Durban. South Africa, 2015. / The planning and management of water resources systems often involve formulation and establishment of optimal operating policies and the study of trade-off between different objectives. Due to the intricate nature of water resources management tasks, several models with varying degrees of complexities have been developed and applied for resolving water resources optimisation and allocation problems. Nevertheless, there still exist uncertainties about finding a generally consistent and trustworthy method that can find solutions which are very close to the global optimum in all scenarios.
This study presents the development and application of a new evolutionary multi-objective optimisation algorithm, combined Pareto multi-objective differential evolution (CPMDE). The algorithm combines methods of Pareto ranking and Pareto dominance selections to implement a novel generational selection scheme. The new scheme provides a systematic approach for controlling elitism of the population which results in the simultaneous creation of short solution vectors that are suitable for local search and long vectors suitable for global search. By incorporating combined Pareto procedures, CPMDE is able to adaptively balance exploitation of non-dominated solutions found with exploration of the search space. Thus, it is able to escape all local optima and converge to the global Pareto-optimal front. The performance of CPMDE was compared with 14 state-of-the-art evolutionary multi-objective optimisation algorithms. A total of ten test problems and three real world problems were considered in the benchmark of the algorithm. Findings suggest that the new algorithm presents an improvement in convergence to global Pareto-optimal fronts especially on deceptive multi-modal functions where CPMDE clearly outperformed all other algorithms in convergence and diversity. The convergence metric on this problem was several orders of magnitude better than those of the other algorithms. Competitive results obtained from the benchmark of CPMDE suggest that it is a good alternative for solving real multi-objective optimisation problems. Also, values of a variance statistics further indicate that CPMDE is reliable and stable in finding solutions and converging to Pareto-optimal fronts in multi-objective optimisation problems.
CPMDE was applied to resolve water allocation problems in the Orange River catchment in South Africa. Results obtained from the applications of CPMDE suggest it represents an improvement over some existing methods. CPMDE was applied to resolve water allocation problems in the agricultural and power sectors in South Africa. These sectors are strategic in forging economic growth, sustaining technological developments and contributing further to the overall development of the nation. They are also germane in capacitating the South African government’s commitment towards equity and poverty eradication and ensuring food security.
Harnessing more hydropower from existing water sources within the frontier of the country is germane in capacitating the South African Government’s commitment to reduction of the countries’ greenhouse gas emissions and transition to a low-carbon economy while meeting a national target of 3 725 megawatts by 2030. Application of CPMDE algorithm in the behavioural analysis of the Vanderkloof reservoir showed an increase of 20 310 MWH in energy generation corresponding to a 3.2 percent increase. On analysis of storage trajectories over the operating period, it was found that the real time analysis incorporating a hybrid between CPMDE and ANN offers a procedure with a high ability to minimize deviation from target storage under the prevailing water stress condition. Overall, the real time analysis provides an improvement of 49.32 percent over the current practice. Further analysis involving starting the simulation with a proposed higher storage volume suggests that 728.53 GWH of annual energy may be generated from the reservoir under medium flow condition without system failure as opposed to 629 GWH produced from current practice. This corresponds to a 13.66 percent increase in energy generation. It was however noted that the water resources of the dam is not in excess. The water in the dam is just enough to meet all current demands. This calls for proper management policies for future operation of the reservoir to guard against excessive storage depletions.
The study herein also involved the development of a decision support system for the daily operation of the Vanderkloof reservoir. This provides a low cost solution methodology suitable for the sustainable operation of the Vanderkloof dam in South Africa. Adopting real time optimisation strategies may be beneficial to the operation of reservoirs. Findings from the study herein indicate that the new algorithm represents an improvement over existing methods. Therefore, CPMDE presents a new tool that nations can adapt for the proper management of water resources towards the overall prosperity of their populace. / D
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Distributed control for collective behaviour in micro-unmanned aerial vehiclesRuini, Fabio January 2013 (has links)
The work presented herein focuses on the design of distributed autonomous controllers for collective behaviour of Micro-unmanned Aerial Vehicles (MAVs). Two alternative approaches to this topic are introduced: one based upon the Evolutionary Robotics (ER) paradigm, the other one upon flocking principles. Three computer simulators have been developed in order to carry out the required experiments, all of them having their focus on the modelling of fixed-wing aircraft flight dynamics. The employment of fixed-wing aircraft rather than the omni-directional robots typically employed in collective robotics significantly increases the complexity of the challenges that an autonomous controller has to face. This is mostly due to the strict motion constraints associated with fixed-wing platforms, that require a high degree of accuracy by the controller. Concerning the ER approach, the experimental setups elaborated have resulted in controllers that have been evolved in simulation with the following capabilities: (1) navigation across unknown environments, (2) obstacle avoidance, (3) tracking of a moving target, and (4) execution of cooperative and coordinated behaviours based on implicit communication strategies. The design methodology based upon flocking principles has involved tests on computer simulations and subsequent experimentation on real-world robotic platforms. A customised implementation of Reynolds’ flocking algorithm has been developed and successfully validated through flight tests performed with the swinglet MAV. It has been notably demonstrated how the Evolutionary Robotics approach could be successfully extended to the domain of fixed-wing aerial robotics, which has never received a great deal of attention in the past. The investigations performed have also shown that complex and real physics-based computer simulators are not a compulsory requirement when approaching the domain of aerial robotics, as long as proper autopilot systems (taking care of the ”reality gap” issue) are used on the real robots.
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[en] QUANTUM-INSPIRED EVOLUTIONARY ALGORITHMS FOR PROBLEMS BASED ON NUMERICAL REPRESENTATION / [pt] ALGORITMOS EVOLUTIVOS COM INSPIRAÇÃO QUÂNTICA PARA PROBLEMAS COM REPRESENTAÇÃO NUMÉRICAANDRE VARGAS ABS DA CRUZ 25 September 2007 (has links)
[pt] Desde que foram propostos como método de otimização, os
algoritmos
evolutivos têm sido usados com sucesso para resolver
problemas complexos
nas mais diversas áreas como, por exemplo, o projeto
automático de circuitos
e equipamentos, planejamento de tarefas, engenharia de
software e mineração
de dados, entre tantos outros. Este sucesso se deve, entre
outras coisas, ao fato
desta classe de algoritmos não necessitar de formulações
matemáticas rigorosas
a respeito do problema que se deseja otimizar, além de
oferecer um alto grau
de paralelismo no processo de busca. No entanto, alguns
problemas são computacionalmente
custosos no que diz respeito à avaliação das soluções
durante o
processo de busca, tornando a otimização por algoritmos
evolutivos um processo
lento para situações onde se deseja uma resposta rápida do
algoritmo (como por
exemplo, problemas de otimização online). Diversas
maneiras de se contornar
este problema, através da aceleração da convergência para
boas soluções, foram
propostas, entre as quais destacam-se os Algoritmos
Culturais e os Algoritmos
Co-Evolutivos. No entanto, estes algoritmos ainda têm a
necessidade de avaliar
muitas soluções a cada etapa do processo de otimização. Em
problemas onde
esta avaliação é computacionalmente custosa, a otimização
pode levar um tempo
proibitivo para alcançar soluções ótimas. Este trabalho
propõe um novo algoritmo
evolutivo para problemas de otimização numérica (Algoritmo
Evolutivo
com Inspiração Quântica usando Representação Real - AEIQ-
R), inspirado no
conceito de múltiplos universos da física quântica, que
permite realizar o processo
de otimização com um menor número de avaliações de
soluções. O trabalho
apresenta a modelagem deste algoritmo para a solução de
problemas benchmark
de otimização numérica, assim como no treinamento de redes
neurais
recorrentes em problemas de aprendizado supervisionado de
séries temporais e
em aprendizado por reforço em tarefas de controle. Os
resultados obtidos demonstram
a eficiência desse algoritmo na solução destes tipos de
problemas. / [en] Since they were proposed as an optimization method, the
evolutionary algorithms
have been successfully used for solving complex problems
in several
areas such as, for example, the automatic design of
electronic circuits and equipments,
task planning and scheduling, software engineering and
data mining,
among many others. This success is due, among many other
things, to the fact
that this class of algorithms does not need rigorous
mathematical formulations
regarding the problem to be optimized, and also because it
offers a high degree of
parallelism in the search process. However, some problems
are computationally
intensive when it concerns the evaluation of solutions
during the search process,
making the optimization by evolutionary algorithms a slow
process for situations
where a quick response from the algorithm is desired (for
instance, in online optimization
problems). Several ways to overcome this problem, by
speeding up
convergence time, were proposed, including Cultural
Algorithms and Coevolutionary
Algorithms. However, these algorithms still have the need
to evaluate
many solutions on each step of the optimization process.
In problems where
this evaluation is computationally expensive, the
optimization might take a prohibitive
time to reach optimal solutions. This work proposes a new
evolutionary
algorithm for numerical optimization problems (Quantum-
Inspired Evolutionary
Algorithm for Problems based on Numerical Representation -
QIEA-R),
inspired in the concept of quantum superposition, which
allows the optimization
process to be carried on with a smaller number of
evaluations. The work presents
the modelling for this algorithm for solving benchmark
numerical optimization
problems, and for training recurrent neural networks in
supervised learning and
reinforcement learning. The results show the good
performance of this algorithm
in solving these kinds of problems.
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[en] HYBRID OPTIMIZATION SYSTEM FOR THE CONTROL STRATEGIES OF INTELLIGENT WELLS UNDER UNCERTAINTIES / [pt] SISTEMA HÍBRIDO DE OTIMIZAÇÃO DE ESTRATÉGIAS DE CONTROLE DE VÁLVULAS DE POÇOS INTELIGENTES SOB INCERTEZASLUCIANA FALETTI ALMEIDA 23 November 2007 (has links)
[pt] A atividade de gerenciamento de reservatórios é uma tarefa
essencial que
visa o desafio da otimização da explotação de reservatórios
de petróleo. Como
resposta a tal desafio a indústria de óleo e gás vem
desenvolvendo novas
tecnologias, como a de poços inteligentes. Esses poços tem
objetivo de baratear
as operações de restaurações mais corriqueiras através do
controle de sua
tecnologia. Assim, este trabalho trata do desenvolvimento
de campos
inteligentes e apresenta um sistema de apoio à decisão
capaz de otimizar,
através de algoritmos evolucionários, o processo de
controle da tecnologia de
poços inteligentes considerando incertezas de falha e
geológica. Além disso, o
sistema se propõe a apoiar na tomada de decisão pelo uso ou
não de poços
inteligentes, dado um reservatório pronto para ser
explorado ou para receber
investimentos de expansão. O controle da tecnologia de
poços inteligentes (IWT
- Intelligent Wells Technology) empregado nesse estudo,
refere-se à operação
de abertura e fechamento dos dispositivos (válvulas)
existentes nesses tipos de
poços. Através da otimização com algoritmos genéticos se
busca uma
estratégia de controle pró-ativo, em outras palavras, agir
antes do efeito, onde se
busca nos tempos iniciais de produção uma configuração de
válvulas que seja
capaz de: atrasar a chegada da frente de água aos poços
produtores, antecipar
a produção de óleo ou melhorar a recuperação de óleo do
campo; em
conseqüência, uma operação que leve à maximização do valor
presente líquido
(VPL). O emprego de estratégias de controle que visam
beneficiar a
completação identifica o campo como inteligente. Outros
trabalhos abordam o
problema de otimização de controle de válvulas em poços
inteligentes, porém
eles utilizam métodos clássicos de otimização que limitam o
número de válvulas
ou ainda otimizam estratégias sem considerar os intervalos
de tempo desejados
para manutenção das válvulas. O modelo evolucionário
empregado nesse
estudo, baseado em algoritmos genéticos, consegue formular
uma estratégia de
controle para todas as válvulas presentes em uma
determinada configuração de produção, em qualquer intervalo
de tempo desejado, atendendo ao critério
econômico de maximizar o VPL. Para apoiar a tomada de
decisão, pelo uso ou
não de poços inteligentes, consideram-se incertezas de
falha e geológica. O
modelo proposto foi avaliado em três reservatórios
petrolíferos, sendo o primeiro
um reservatório sintético, e os outros dois reservatórios
mais complexos com
características mais próximas das reais. Os resultados
encontrados indicam que
o modelo proposto permite alcançar boas estratégias de
controle que levam a
um aumento do VPL. A principal contribuição deste trabalho
é a concepção e
implementação de um sistema baseado em técnicas
inteligentes capaz de apoiar
no desenvolvimento e gerenciamento de reservatórios
petrolíferos inteligentes
considerando incertezas. / [en] The reservoir management is an important task that aims at
the
optimization of oil reservoir exploitation. To support this
challenging mission, the
oil and gas industry has been developing new technologies
such as intelligent
wells. The purpose of these wells is to reduce costs of the
most common
restoring operations by control of their actuators. Thus,
this work deals with
intelligent fields development and presents a decision
support system able to
optimize, by using evolutionary algorithms, the intelligent
wells technology control
process considering geological and technical uncertainties.
In addition, the
system gives support for the decision of rather to use or
not intelligent wells,
given a reservoir ready to be explored or to receive
expansion investments. The
control of Intelligent Wells Technology (IWT), as applied
in this study, refers to
the opening and closing operations of valves in these types
of wells. An
optimization based on genetic algorithms is used to produce
a pro-active control
strategy, that is, one that anticipates the actions to be
taken in present time in
order to achieve better results in the future. Such a
strategy proposes a valve
configuration that will be able to: delay the water cut on
producer wells, advance
the oil production or benefit the oil recuperation. As a
result, the obtained
configuration leads to a maximization of the NPV (Net
Present Value). The usage
of control strategies that aim to benefit completion
identifies the oil field as
intelligent. Other works also deal with valve control
optimization problems in
intelligent wells. However, they use classical optimization
methods; these
methods limit the number of valves or optimize strategies
without considering
time. The evolutionary model, based on genetic algorithm,
applied in this study,
can formulate a control strategy for all valves in a
certain production
configuration, for any desired time interval, according to
the economical criteria of
NPV maximization. In order to support the decision making
for the use or not of
intelligent wells, technical and geological uncertainties
are considered. The
proposed model was evaluated in three oil reservoirs. The
first one is a synthetic
reservoir, simple and not real; the other two are more
complex with close to real characteristics. The results
obtained indicate that the proposed model allows
good control strategies that increase the NPV. The main
contribution of this work
is the conception and implementation of a system based on
intelligent techniques
that is able to support the development and management of
intelligent oil
reservoirs considering uncertainties.
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Método de análise para a coordenação dos processos de produção sob a ótica de redes de inovação colaborativas apoiado por agente inteligente evolutivoCarvalho, Heber Lombardi de 31 August 2012 (has links)
No contexto da engenharia de produção a pesquisa analisa a coordenação do processo de produção. As principais frentes de gerentes de planejamento e de controladoria são o atendimento à demanda do mercado e os custos de produção divergentes em relação ao plano inicial. Verifica-se que há uma lacuna processual entre dois processos organizacionais, a análise de controladoria direcionada a custos realizados e a análise de planejamento e controle da produção voltada ao atendimento da demanda. A assimetria do uso do mesmo conjunto de dados com visões críticas distintas, contudo com intenções finais similares, motivam o trabalho. Levanta-se a hipótese da análise dos dados com fundamentação conceitual estruturada para abranger a rede de colaboração produtiva. O objetivo é, então, estabelecer um método de análise para a coordenação do processo de produção, elaborado sob a ótica de redes de inovação colaborativas apoiado por agente inteligente evolutivo. A fundamentação conceitual da coordenação do processo de produção, da inovação e da função de produção compõem a estrutura da revisão literária. Pelo método de pesquisa, sob o recorte analítico de vertentes teóricas de redes, uma inovação promovida pela pesquisa foi o mapeamento e a associação de variáveis processuais internas ao nó principal da rede aos nós processuais externos. Uma aplicação tecnológica comercial não é suficiente para interpretar esse ambiente dinâmico e orientado à mudança. O algoritmo DAMICORE, sob a égide evolutiva da biologia, encontra nós homólogos e interpreta o rótulo dos nós processuais validados em campo. O novo método de análise para a coordenação do processo de produção é aferido em rede por um projeto piloto e replicado, então, em vinte e uma redes com resultados melhores comparativamente ao método tradicional. Assim, a pesquisa cria um novo paradigma de análise para processos em rede e demonstra a representatividade de variáveis associadas a nós processuais, desde que eleitas conceitualmente e validadas por especialistas da área. / In the industrial engineering context this research examines the coordination of production process. The main concerns of planning managers and controllers are the demand oscillation and deviation of budget production costs. There is a lack between two processes, the controlling analysis aimed at real costs and planning analysis aimed at demand. The motivation of this work is the asymmetry of the use of the same data set from different perspectives but with similar goals. It is possible to elaborate the hypothesis to analyse of structured data with the conceptual basis to study the cooperative network. The goal is to establish a method of analysis for the coordination of production process systematized from the perspective of innovation collaborative networks where this method is compiled by evolutionary concepts with an intelligent agent application. The literature review comprises the coordination of production process, the innovation concepts and the production function concepts. The method of research applies variables belonging to internal process to external process from principal network node, this approach it is done under the analytical of theoretical networks basis. The method of research is designed to find variables belonging to internal process to relate to external process variables from principal network node, this approach it is done under the analytical of theoretical networks basis. This way has promoted a innovation for the work. A commercial technological application is not enough to mining data set from this dynamic and change oriented environment. The DAMICORE algorithm under the evolutionary concepts from biology area can find correlated nodes validated with the field data. The new method of analysis for the coordination of production process is adjusted by a pilot project then it is replicated in twenty-one networks with amazing results when compared to the current method. The research creates a new paradigm for process analysis and demonstrates the variables power representation and association from network processes if they are under conceptual basis to validate by experts.
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[en] SYNTHESIS OF FUZZY SYSTEMS THROUGH EVOLUTIONARY COMPUTATION / [pt] SÍNTESE DE SISTEMAS FUZZY POR COMPUTAÇÃO EVOLUCIONÁRIAJOSE FRANCO MACHADO DO AMARAL 30 May 2003 (has links)
[pt] Síntese de Sistemas Fuzzy por Computação Evolucionária
propõe uma metodologia de projeto para o desenvolvimento
de
sistemas fuzzy fundamentada em técnicas de computação
evolucionária. Esta metodologia contempla as etapas
de concepção do sistema fuzzy e a implementação em
hardware
do circuito eletrônico que o representa. A concepção do
sistema é realizada num ambiente de projeto no qual sua
base de conhecimento - composta da base de regras e demais
parâmetros característicos - é evoluída, por intermédio
de
simulação, através do emprego de um novo algoritmo de
três
estágios que utiliza Algoritmos Genéticos. Esta
estratégia
enfatiza a interpretabilidade e torna a criação do
sistema
fuzzy mais simples e eficiente para o projetista,
especialmente quando comparada com o tradicional ajuste
por
tentativa e erro. A implementação em hardware do circuito
é realizada em plataforma de desenvolvimento baseada em
Eletrônica Evolucionária. Um conjunto de circuitos,
denominados de blocos funcionais, foi desenvolvido e
evoluído com sucesso para viabilizar a construção da
estrutura final do sistema fuzzy. / [en] Synthesis of Fuzzy Systems through Evolutionary Computation
proposes a methodology for the design of fuzzy systems
based on evolutionary computation techniques. A three-stage
evolutionary algorithm that uses Genetic Algorithms
(GAs) evolves the knowledge base of a fuzzy system - rule
base and parameters. The evolutionary aspect makes the
design simpler and more efficient, especially when compared
with traditional trial and error methods. The method
emphasizes interpretability so that the resulting strategy
is clearly stated. An Evolvable Hardware (EHW) platform for
the synthesis of analog electronic circuits is proposed.
This platform, which can be used for the implementation of
the designed fuzzy system, is based on a Field Programmable
Analog Array (FPAA). A set of evolved circuits called
functional blocks allows the implementation of the
fuzzy system.
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Método de análise para a coordenação dos processos de produção sob a ótica de redes de inovação colaborativas apoiado por agente inteligente evolutivoHeber Lombardi de Carvalho 31 August 2012 (has links)
No contexto da engenharia de produção a pesquisa analisa a coordenação do processo de produção. As principais frentes de gerentes de planejamento e de controladoria são o atendimento à demanda do mercado e os custos de produção divergentes em relação ao plano inicial. Verifica-se que há uma lacuna processual entre dois processos organizacionais, a análise de controladoria direcionada a custos realizados e a análise de planejamento e controle da produção voltada ao atendimento da demanda. A assimetria do uso do mesmo conjunto de dados com visões críticas distintas, contudo com intenções finais similares, motivam o trabalho. Levanta-se a hipótese da análise dos dados com fundamentação conceitual estruturada para abranger a rede de colaboração produtiva. O objetivo é, então, estabelecer um método de análise para a coordenação do processo de produção, elaborado sob a ótica de redes de inovação colaborativas apoiado por agente inteligente evolutivo. A fundamentação conceitual da coordenação do processo de produção, da inovação e da função de produção compõem a estrutura da revisão literária. Pelo método de pesquisa, sob o recorte analítico de vertentes teóricas de redes, uma inovação promovida pela pesquisa foi o mapeamento e a associação de variáveis processuais internas ao nó principal da rede aos nós processuais externos. Uma aplicação tecnológica comercial não é suficiente para interpretar esse ambiente dinâmico e orientado à mudança. O algoritmo DAMICORE, sob a égide evolutiva da biologia, encontra nós homólogos e interpreta o rótulo dos nós processuais validados em campo. O novo método de análise para a coordenação do processo de produção é aferido em rede por um projeto piloto e replicado, então, em vinte e uma redes com resultados melhores comparativamente ao método tradicional. Assim, a pesquisa cria um novo paradigma de análise para processos em rede e demonstra a representatividade de variáveis associadas a nós processuais, desde que eleitas conceitualmente e validadas por especialistas da área. / In the industrial engineering context this research examines the coordination of production process. The main concerns of planning managers and controllers are the demand oscillation and deviation of budget production costs. There is a lack between two processes, the controlling analysis aimed at real costs and planning analysis aimed at demand. The motivation of this work is the asymmetry of the use of the same data set from different perspectives but with similar goals. It is possible to elaborate the hypothesis to analyse of structured data with the conceptual basis to study the cooperative network. The goal is to establish a method of analysis for the coordination of production process systematized from the perspective of innovation collaborative networks where this method is compiled by evolutionary concepts with an intelligent agent application. The literature review comprises the coordination of production process, the innovation concepts and the production function concepts. The method of research applies variables belonging to internal process to external process from principal network node, this approach it is done under the analytical of theoretical networks basis. The method of research is designed to find variables belonging to internal process to relate to external process variables from principal network node, this approach it is done under the analytical of theoretical networks basis. This way has promoted a innovation for the work. A commercial technological application is not enough to mining data set from this dynamic and change oriented environment. The DAMICORE algorithm under the evolutionary concepts from biology area can find correlated nodes validated with the field data. The new method of analysis for the coordination of production process is adjusted by a pilot project then it is replicated in twenty-one networks with amazing results when compared to the current method. The research creates a new paradigm for process analysis and demonstrates the variables power representation and association from network processes if they are under conceptual basis to validate by experts.
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An online and adaptive signature-based approach for intrusion detection using learning classifier systemsShafi, Kamran, Information Technology & Electrical Engineering, Australian Defence Force Academy, UNSW January 2008 (has links)
This thesis presents the case of dynamically and adaptively learning signatures for network intrusion detection using genetic based machine learning techniques. The two major criticisms of the signature based intrusion detection systems are their i) reliance on domain experts to handcraft intrusion signatures and ii) inability to detect previously unknown attacks or the attacks for which no signatures are available at the time. In this thesis, we present a biologically-inspired computational approach to address these two issues. This is done by adaptively learning maximally general rules, which are referred to as signatures, from network traffic through a supervised learning classifier system, UCS. The rules are learnt dynamically (i.e., using machine intelligence and without the requirement of a domain expert), and adaptively (i.e., as the data arrives without the need to relearn the complete model after presenting each data instance to the current model). Our approach is hybrid in that signatures for both intrusive and normal behaviours are learnt. The rule based profiling of normal behaviour allows for anomaly detection in that the events not matching any of the rules are considered potentially harmful and could be escalated for an action. We study the effect of key UCS parameters and operators on its performance and identify areas of improvement through this analysis. Several new heuristics are proposed that improve the effectiveness of UCS for the prediction of unseen and extremely rare intrusive activities. A signature extraction system is developed that adaptively retrieves signatures as they are discovered by UCS. The signature extraction algorithm is augmented by introducing novel subsumption operators that minimise overlap between signatures. Mechanisms are provided to adapt the main algorithm parameters to deal with online noisy and imbalanced class data. The performance of UCS, its variants and the signature extraction system is measured through standard evaluation metrics on a publicly available intrusion detection dataset provided during the 1999 KDD Cup intrusion detection competition. We show that the extended UCS significantly improves test accuracy and hit rate while significantly reducing the rate of false alarms and cost per example scores than the standard UCS. The results are competitive to the best systems participated in the competition in addition to our systems being online and incremental rule learners. The signature extraction system built on top of the extended UCS retrieves a magnitude smaller rule set than the base UCS learner without any significant performance loss. We extend the evaluation of our systems to real time network traffic which is captured from a university departmental server. A methodology is developed to build fully labelled intrusion detection dataset by mixing real background traffic with attacks simulated in a controlled environment. Tools are developed to pre-process the raw network data into feature vector format suitable for UCS and other related machine learning systems. We show the effectiveness of our feature set in detecting payload based attacks.
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