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Muzikos mokyklų mokinių nesėkmingo mokymosi priežastys ir jų šalinimo galimybės / The reasons of unsuccessful learning of music school children and the possibilities of their eliminationGudienė, Lina 20 June 2006 (has links)
The analytic review of the literature lets do the theoretical providence, that the change of art developing is going too slow and too little correspond the needs of quickly changing society. It is actual to analyze the existing situation and look for the new ideas how to optimize MS’ activity by democratizing, humanizing the process of development and seeking to make the modern effective and improving non- formal educational organization.
The purpose of survey – is to highlight the reasons of unsuccessful (self) learning of MS’ children and the possibilities of their elimination.
In this work were used the following methods of fact-finding: analysis of theoretical – scientific literature, analysis of documents; empirical – questionnaires. The purpose of ques-tionnaires – is to investigate the point of view of respondents towards the process of development in MS, to reveal the providence of developing process and optimizing the content using the mod-ern experience of education management (the principles of change proposed by the general qual-ity management and after creative modification of 14 management responsibilities of W. Dem-ing). In the onetime quantitative estimative survey participated teachers from 5 music schools and schoolchildren of 1-7 classes from the same schools. Also was done the qualitative questioning analysis of parents of former pupils of music schools.
With reference to the data of survey it can be maintained, that most often cases of unsuccessful... [to full text]
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Swinging Babe's Bat: Optimizing Home Run Distance Using Ideal ParametersShore, Patrick 01 January 2019 (has links)
Significant research has been conducted on the physics of ball and bat collisions in an effort to model and understand real-world conditions. This thesis expands upon previous research to determine the maximum distance a ball can travel under ideal circumstances. Bat mass, bat speed, pitch speed and pitch spin were controlled values. These values were selected based on the highest recorded MLB values for their respective category. Specifically these are: Babe Ruth’s largest bat, Giancarlo Stanton’s recorded swing speed and Aroldis Chapman’s fastest fastball. A model was developed for a planar collision between a bat and ball using conservation laws in order to achieve the maximum exit velocity of the ball during a head-on collision. However, this thesis is focused on home runs and long fly-balls that occur from oblique collisions rather than the line drives produced by head-on collisions. The planar collision model results were adjusted to oblique collisions based on data from previous experimental research. The ball and bat were assumed to be moving in opposite directions parallel to one another at the point of impact with the ball slightly elevated above the bat. The post-collision results for the launch angle, spin and final exit velocity of the ball were calculated as functions of the perpendicular distance from the centerline of the bat to the centerline of the ball. Trajectories of the ball were calculated using a flight model that measured the final distance of the ball based on lift and drag forces. The results indicate that the optimum pre-collision parameters described above will maximize the distance traveled by the ball well beyond the farthest recorded home run distance. Experimentally determined factors such as the drag coefficient and coefficient of restitution have a significant impact on the flight of the ball. Implications of the results are discussed.
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Analyzing pressure and temperature data from smart plungers to optimize lift cyclesChava, Gopi Krishna 15 May 2009 (has links)
The problem of liquid loading is common for all gas producing wells and should be
identified and solved for efficient gas production. Production engineers and operators
need to choose the best solution possible, one that is cost effective and also efficient in
doing the job. The plunger lift operation is a cost-effective solution to this liquid loading
problem and also is efficient in increasing the gas production. However, the current
understanding of plunger lift operation has used field experience and some previous
models that have restrictive assumptions which might not be applicable for all plunger lift
installations. This research proposes a new plunger lift model that overcomes some of the
limiting assumptions of earlier models by using additional data available in the form of
pressure and temperature from new technology like smart plunger. The model is based on
fundamental principles of mass conservation and pressure balance, and uses the smart
plunger data as input. The implementation of the model is carried out in user-friendly and
easily accessible software like Excel VBA (Visual Basic Applications). The model
predicts the plunger velocity, plunger position and annulus liquid level during an upward
travel of the plunger in an onshore gas well in East Texas. The results of model
implementation in VBA show the importance of fluid properties for the model, apart from indicating that the model is optimized for the given set of input data. The model
developed in this research considers only pressure drop due to gravitational effects, and
thus provides a scope for improvement in modeling the plunger lift dynamics by adding
frictional and acceleration components. This research also provides recommendations for
future work that can be carried out on plunger lift modeling using smart plungers.
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Neural Networks Performance and Structure Optimization Using Genetic AlgorithmsKopel, Ariel 01 August 2012 (has links) (PDF)
Artificial Neural networks have found many applications in various fields such as function approximation, time-series prediction, and adaptive control. The performance of a neural network depends on many factors, including the network structure, the selection of activation functions, the learning rate of the training algorithm, and initial synaptic weight values, etc.
Genetic algorithms are inspired by Charles Darwin’s theory of natural selection (“survival of the fittest”). They are heuristic search techniques that are based on aspects of natural evolution, such as inheritance, mutation, selection, and crossover.
This research utilizes a genetic algorithm to optimize multi-layer feedforward neural network performance and structure. The goal is to minimize both the function of output errors and the number of connections of network. The algorithm is modeled in C++ and tested on several different data sets. Computer simulation results show that the proposed algorithm can successfully determine the appropriate network size for optimal performance. This research also includes studies of the effects of population size, crossover type, probability of bit mutation, and the error scaling factor.
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Optimised dose titration for Duodopatreatment based on simulation experiments– implementation in a decision supportsystemCHen, Canghai January 2009 (has links)
The aim of this work was to design a set of rules for levodopa infusion dose adjustment in Parkinson’s disease based on a simulation experiments. Using this simulator, optimal infusions dose in different conditions were calculated. There are seven conditions (-3 to +3)appearing in a rating scale for Parkinson’s disease patients. By finding mean of the differences between conditions and optimal dose, two sets of rules were designed. The set of rules was optimized by several testing. Usefulness for optimizing the titration procedure of new infusion patients based on rule-based reasoning was investigated. Results show that both of the number of the steps and the errors for finding optimal dose was shorten by new rules. At last, the dose predicted with new rules well on each single occasion of majority of patients in simulation experiments.
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Design and Optimization of Ultrafiltration Membrane Setup for Wastewater Treatment and Reuse / Optimering av en membranfiltreringsprocess för avloppsvattenrening och återanvändningSharma, Ekansh January 2020 (has links)
With the advances in the membrane technology, there is an ongoing quest to determine the best optimal configuration for an adopted treatment as well as it’s polishing to achieve cumulative sustainability for the treatment process. Henceforth, this thesis report is an evaluation to devise a membrane filtration process for investigating the possibility of treating pre-sedimented municipal wastewater with ceramic ultrafiltration, optimizing the membrane as a pre-treatment for reverse osmosis as an overall strategy for recovering wastewater. Methods and various technological trends pertaining to membrane filtration of municipal wastewater were researched and documented, Interestingly the five most influential factors governing the membrane performance are identified: 1) Back pulsing Frequency 2) VRF 3) Run Time 4) Cross-Flow Rate 5) Trans Membrane Pressure (TMP). To get a thorough and holistic overview of parametric influence design of experiment (DOE) is devised to find the influence of above-given factors on outcoming responses as COD Reduction (%), Membrane Flux and Turbidity reduction (%). 16+3 DOE factorial tests are executed at Hammarby Sjöstadsverk, Joint Research Facility of IVL Swedish Environmental Research Institute & KTH Royal Institute of Technology on pilot plant WASLA incorporating an ATECH GmBh 20kDa, Type 7/6 Ultrafiltration membrane module where Factorial experiments resulted in a maximum value of flux of 274 LMH, 88.75% reduction of COD and 99.94% reduction of Turbidity. Moreover, response values obtained from the Results of factorial experiments are fed in MODDE, generating a model using PLS Regression, The model summary presented predictivity and reproducibility trends w.r.t responses used. Furthermore, COD resulted in the worst fit followed by Turbidity, and the best fit was observed for Membrane Flux where model fit represented the ability to predict the respective parameter. Optimization tool is utilised to simulate a case scenario where the Membrane flux response is maximized to a high value of 300 LMH and correspondingly 211.885 LMH value is recorded, Furthermore factor influence is identified to be TMP> VRF> Cross Flow >BP Frequency >Runtime. Overall COD reductions are found out to be heavily influenced by the varying incoming feed therefore it is hard to analyze their interactions and predict their subsequent reduction behavior. Back pulsing overall was found out to be another non-influential factor colluding with results throughout the experimental duration with very little or no effect on the permeate water quality. / Med framstegen inom membrantekniken finns det en kontinuerlig strävan att fastställa bästa optimala konfigurationen för en antagen behandling samt att den är polerad för att uppnå kumulativ hållbarhet för behandlingsprocessen. Framgent är denna avhandlingsrapport en utvärdering för att utforma en membranfiltreringsprocess för att undersöka möjligheten att behandla försedimenterat kommunalt avloppsvatten med keramisk ultrafiltrering, optimera membranet som en förbehandling för omvänd osmos som en övergripande strategi för att återvinna avloppsvatten. Metoder och olika teknologiska trender avseende membranfiltrering av kommunalt avloppsvatten undersöktes och dokumenterades. Intressant identifieras fem mest inflytelserika faktorer som styr membranprestanda: 1) Ryggpulserande frekvens 2) VRF 3) Körtid 4) Korsflödeshastighet 5) Trans Membrantryck (TMP). För att få en grundlig och holistisk överblick över parametrisk inflytande experimentet är utformat för att hitta påverkan av ovan givna faktorer på utgående svar som COD- Reduktion (%), Membranflöde och Turbiditetsreduktion (%). 16 + 3 DOE-faktortest utfördes vid Hammarby Sjöstadsverk, Joint Research Facility för IVL Swedish Environmental Research Institute & KTH Royal Institute of Technology på pilotanläggningen WASLA med en ATECH GmBh 20kDa, typ 7/6 Ultrafiltreringsmembranmodul där faktoriella experiment resulterade i en maximalt flödesvärde på 274 LMH, 88,75% reduktion av COD och 99,94% reduktion av turbiditet. Moreover, response values obtained from the Results of factorial experiments are fed in MODDE, generating a model using PLS Regression, The model summary presented predictivity and reproducibility trends w.r.t responses used. Furthermore, COD resulted in the worst fit followed by Turbidity, and the best fit was observed for Membrane Flux where model fit represented the ability to predict the respective parameter. Optimization tool is utilised to simulate a case scenario where the Membrane flux response is maximized to a high value of 300 LMH and correspondingly 211.885 LMH value is recorded, Furthermore factor influence is identified to be TMP> VRF> Cross Flow >BP Frequency >Runtime. Overall COD reductions are found out to be heavily influenced by the varying incoming feed therefore it is hard to analyze their interactions and predict their subsequent reduction behavior. Back pulsing overall was found out to be another non-influential factor colluding with results throughout the experimental duration with very little or no effect on the permeate water quality.
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A CAD approach to optimize underground mine design and planningSridhar, Chaluvadi K. January 1986 (has links)
No description available.
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Dynamic Optimization of Multi-Unit Systems Under Failure ConditionsBalthazaar, Anthony 08 1900 (has links)
Shutdowns in a chemical processing plant are detrimental both to plant economics and critical product characteristics. These situations can be due to routine maintenance, or due to the more extreme case of equipment failure due to wear. Nevertheless, both are cases of non-normal plant operation, and are often unavoidable. These situations are complicated further when many units are linked, and subjected to a high degree of integration. In this case, the shutdown of any unit within the plant can have immediate and potentially severe impacts on other areas of the operation. Since these events are unavoidable, the challenge is to minimize their economic impact through careful design of operating practices, and potentially plant design retrofits. This thesis focuses on developing generic and systematic methods of determining economically optimal operating policies and plant designs in the face of failures in multi-unit operations. This includes determining the optimal trajectory of critical plant variables (flows through units, flows between units, buffer tank levels, etc.), as well as determining whether plant design changes would improve plant economics during such events. Such ventures lead to mixed-integer dynamic optimization (MIDO) problems. A dynamic model of the process is presented, accounting for the major flows of process materials through units, between units, as well as the accumulation of these in the intermediate buffer capacities. The approach used was to assume that the processing units operated at pseudo-steady-state, with dynamics confined to the intermediate buffer capacities. All models developed were based on a combination of empirical and fundamental elements. For use of the model in an optimization study, a simultaneous approach, in which the differential equations are discretized and included as equality constraints, was employed. This yielded a nonlinear optimization problem involving only algebraic equations. Optimal responses to scenarios involving planned maintenance shutdowns, as well as unplanned shutdowns (unit failures) were computed, with plant economics used as the merit function. Sensitivity to parameters such as preparation time, shutdown length, and restoration time were studied. In all cases, it was desired to maximize plant economics, while maintaining a smooth operation. While several methods are available for use in a multi-criterion optimization problem, a two-tiered approach was developed and applied in which the plant economics were maximized first, and input usage subsequently minimized as a secondary objective. After identifying key failure scenarios through a review of industrial data and downtime reports, a multiple-model formulation was developed involving the probability distribution of failure scenarios. Optimal steady-state operating levels for the buffer capacities were computed. This formulation is then extended to a mixed-integer programming problem in which the addition of extra buffer capacity is included as a decision variable. / Thesis / Master of Applied Science (MASc)
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Modelos matemáticos e heurísticas baseadas em técnicas de programação matemática para o problema de minimização de perdas e reconfiguração de redes elétricas / Mathematical models and heuristic based on mathematical programming techniques for the problem of minimization of losses and reconfiguration of electrical networksSpatti, Karla Barbosa de Freitas 04 April 2018 (has links)
A reconfiguração de redes de distribuição de energia elétrica consiste em alterar sua topologia por meio de manobras de chaves nos circuitos primários. Trata-se de um problema de otimização combinatória, onde normalmente os objetivos são a minimização de perdas ativas e/ou número de manobras realizadas, atendendo as restrições como isolamento de faltas, balanceamento de cargas entre os alimentadores e melhoria dos níveis de tensão. As dificuldades na modelagem e na resolução exata de problemas envolvendo a reconfiguração de redes de distribuição advém do tamanho dos sistemas reais, representados por um número elevado de chaves e alimentadores e ainda pela natureza combinatorial do problema. Para tratar essas questões, diversas modelagens e técnicas computacionais têm sido desenvolvidas, em particular heurísticas de melhoramento que através de uma solução factível, otimiza os resultados reduzindo o espaço de busca, até encontrar uma nova solução com melhor função objetivo. Neste sentido, são propostas duas formulações matemáticas descrevendo novas restrições a fim de melhorar a descrição do problema. A primeira, uma formulação mais simplificada, considera apenas a parte ativa das instâncias; na segunda um modelo completo é descrito otimizando parte das restrições do primeiro modelo e considerando também a parte reativa das instâncias. Duas heurísticas também são adaptadas pela primeira vez para o problema de reconfiguração de redes, pois a heurística de melhoramento Fix-and-Optmize é configurada de duas formas diferentes, determinando seus principais parâmetros através de uma análise de sensibilidade. Os resultados dos dois modelos propostos e também das heurísticas adaptadas para 13 sistemas de referência são descritos e comparados com outros métodos da literatura. Para verificar a eficiência e robustez dos métodos e heurísticas desenvolvidos, replicações são propostas de dois sistemas de referência, 9 replicações do sistema de 72 barras e 4 replicações do sistema de 10560 barras. Seus resultados bem como o desempenho dos métodos são descritos e avaliados. / A reconfiguration of electricity distribution networks consists in altering a topology of the networks by means of key maneuvers in the primary circuits. It is a problem of combinatorial optimization, where the objectives are a minimization of active losses and/or number of maneuvers performed, taking into account constraints such as fault isolation, load balance between feeders and improvement of voltage levels. As difficulties in modeling and in the exact resolution of problems involving a reconfiguration of distribution networks come from the size of the real systems, represented by a large number of switches and feeders, and also by the combinatorial nature of the problem. To address these issues, several models and computational techniques have been developed, in particular heuristics of improvement that through a feasible solution, improves results by reducing the search space, until finding a new solution with better objective function. In this sense, in this thesis it is proposed of two mathematical formulations describing new constraints in order to improve a description of the problem. A first, simpler formulation considers only a active part of the instances, in the second a complete model is described optimizing some restrictions of the first model and also considering the reactive part of the instances. Two heuristics are also first adapted to the network reconfiguration problem. The Fix-and-Optmize enhancement heuristic is configured in two different ways, determining its key parameters through a sensitivity analysis. The results of the two proposed models and also of the heuristics adapted for 13 reference systems are described and compared with other methods of the literature. To verify the efficiency and robustness of the developed methods and heuristics, replications are proposed for two reference systems, 9 replications of the 72 bus system and 4 replications of the 10560 bus system. Its results as well as the performance of the methods are described and evaluated.
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Modelos matemáticos e heurísticas baseadas em técnicas de programação matemática para o problema de minimização de perdas e reconfiguração de redes elétricas / Mathematical models and heuristic based on mathematical programming techniques for the problem of minimization of losses and reconfiguration of electrical networksKarla Barbosa de Freitas Spatti 04 April 2018 (has links)
A reconfiguração de redes de distribuição de energia elétrica consiste em alterar sua topologia por meio de manobras de chaves nos circuitos primários. Trata-se de um problema de otimização combinatória, onde normalmente os objetivos são a minimização de perdas ativas e/ou número de manobras realizadas, atendendo as restrições como isolamento de faltas, balanceamento de cargas entre os alimentadores e melhoria dos níveis de tensão. As dificuldades na modelagem e na resolução exata de problemas envolvendo a reconfiguração de redes de distribuição advém do tamanho dos sistemas reais, representados por um número elevado de chaves e alimentadores e ainda pela natureza combinatorial do problema. Para tratar essas questões, diversas modelagens e técnicas computacionais têm sido desenvolvidas, em particular heurísticas de melhoramento que através de uma solução factível, otimiza os resultados reduzindo o espaço de busca, até encontrar uma nova solução com melhor função objetivo. Neste sentido, são propostas duas formulações matemáticas descrevendo novas restrições a fim de melhorar a descrição do problema. A primeira, uma formulação mais simplificada, considera apenas a parte ativa das instâncias; na segunda um modelo completo é descrito otimizando parte das restrições do primeiro modelo e considerando também a parte reativa das instâncias. Duas heurísticas também são adaptadas pela primeira vez para o problema de reconfiguração de redes, pois a heurística de melhoramento Fix-and-Optmize é configurada de duas formas diferentes, determinando seus principais parâmetros através de uma análise de sensibilidade. Os resultados dos dois modelos propostos e também das heurísticas adaptadas para 13 sistemas de referência são descritos e comparados com outros métodos da literatura. Para verificar a eficiência e robustez dos métodos e heurísticas desenvolvidos, replicações são propostas de dois sistemas de referência, 9 replicações do sistema de 72 barras e 4 replicações do sistema de 10560 barras. Seus resultados bem como o desempenho dos métodos são descritos e avaliados. / A reconfiguration of electricity distribution networks consists in altering a topology of the networks by means of key maneuvers in the primary circuits. It is a problem of combinatorial optimization, where the objectives are a minimization of active losses and/or number of maneuvers performed, taking into account constraints such as fault isolation, load balance between feeders and improvement of voltage levels. As difficulties in modeling and in the exact resolution of problems involving a reconfiguration of distribution networks come from the size of the real systems, represented by a large number of switches and feeders, and also by the combinatorial nature of the problem. To address these issues, several models and computational techniques have been developed, in particular heuristics of improvement that through a feasible solution, improves results by reducing the search space, until finding a new solution with better objective function. In this sense, in this thesis it is proposed of two mathematical formulations describing new constraints in order to improve a description of the problem. A first, simpler formulation considers only a active part of the instances, in the second a complete model is described optimizing some restrictions of the first model and also considering the reactive part of the instances. Two heuristics are also first adapted to the network reconfiguration problem. The Fix-and-Optmize enhancement heuristic is configured in two different ways, determining its key parameters through a sensitivity analysis. The results of the two proposed models and also of the heuristics adapted for 13 reference systems are described and compared with other methods of the literature. To verify the efficiency and robustness of the developed methods and heuristics, replications are proposed for two reference systems, 9 replications of the 72 bus system and 4 replications of the 10560 bus system. Its results as well as the performance of the methods are described and evaluated.
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