<p>Synthesizing the realistic motion of a humanoid is a very sophisticated task, studied in different research areas. This work addresses the problem to synthetize realistic animations of 3D biped characters in a simulated environment, using genetic algorithms. Characters are represented as a structure of rigid bodies linked each other by 1DOF joints. Such joints are controlled by sinusoidal functions whose parameters are calculated by the genetic algorithm. Results, obtained by testing and comparing several different genetic operators, are presented. The system we have created allows the non-skilled user, to automatically create animations by setting only few key-poses of the characters.</p>

<p>This research project studies the feasibility of developing and applying an integrated field simulator to simulate the production performance of an entire oil or gas field. It integrates the performance of the reservoir, the wells, the chokes, the gathering system, the surface processing facilities and, whenever applicable, gas and water injection systems.</p><p>The approach adopted for developing the integrated simulator is to couple existing commercial reservoir and process simulators using available linking technologies. The simulators are dynamically linked and customized into a single hybrid application that benefits from the concept of open software architecture. The integrated field simulator is linked to an optimization routine developed based on the genetic algorithm search strategies. This enables optimization of the system at field level, from the reservoir to the process. Modeling the wells and the gathering network is achieved by customizing the process simulator.</p><p>This study demonstrates that the integrated simulation improves currentcapabilities to simulate the performance of an entire field and optimize its design. This is achieved by evaluating design options including spread and layout of the wells and gathering system, processing alternatives, reservoir development schemes, and production strategies.</p><p>Effectiveness of the integrated simulator is demonstrated and tested through several field-level case studies that discuss and investigate technical problems relevant to offshore field development. The case studies cover topics such as process optimization, optimum tie-in of satellite wells into existing process facilities, optimal well location, and field layout assessment of a high pressure high temperature deepwater oil field.</p><p>Case study results confirm the viability of the total field simulator by demonstrating that the field performance simulation and optimal design were obtained in an automated process with reasonable computation time. No significant simplifying assumptions were required to solve the system and tedious manual data transfer between simulators, as conventionally practiced, was avoided.</p>

Modifiable Boltzmann selective pressure is investigated as a tool to control variability in optimizations using genetic algorithms. An implementation of variable selective pressure, modeled after the use of temperature as a parameter in simulated annealing approaches, is described. The convergence behavior of optimization runs is illustrated as a function of selective pressure; the method is compared to a genetic algorithm lacking this control feature and is shown to exhibit superior convergence properties on a small set of test problems. An analysis is presented that compares the selective pressure of this algorithm to a standard selection procedure.

Thesis (Ph.D.)--Wichita State University, 2003. / Adviser: Ravi Pendse. Includes bibliographical references.

The Power System Automation Lab at Texas A&M University developed a fault location scheme that can be used for radial distribution systems. When a fault occurs, the scheme executes three stages. In the first stage, all data measurements and system information is gathered and processed into suitable formats. In the second stage, three fault location methods are used to assign possibility values to each line section of a feeder. In the last stage, a fuzzy resolver is used to aggregate the outputs of the three fault location methods and assign a final possibility value to each line section of a feeder. By aggregating the outputs of the three fault location methods, the fuzzy resolver aims to obtain a smaller subset of line sections as potential faulted sections than the individual fault location methods. Fuzzy aggregation operators are used to implement fuzzy resolvers. This dissertation reports on a methodology that was developed utilizing fuzzy aggregation operators in the fuzzy resolver. Three fuzzy aggregation operators, the min, OWA, and uninorm, and two objective functions were used to design the fuzzy resolver. The methodologies to design fuzzy resolvers with respect to a single objective function and with respect to two objective functions were presented. A detailed illustration of the design process was presented. Performance studies of designed fuzzy resolvers were also performed. In order to design and validate the fuzzy resolver methodology, data were needed. Due to the lack of real field data, simulating a distribution feeder was a feasible alternative to generate data. The IEEE 34 node test feeder was modeled. Time current characteristics (TCC) based protective devices were added to this feeder. Faults were simulated on this feeder to generate data. Based on the performance studies of designed fuzzy resolvers, the fuzzy resolver designed using the uninorm operator without weights is the first choice. For this fuzzy resolver, no optimal weights are needed. In addition, fuzzy resolvers using the min operator and OWA operator can be used to design fuzzy resolvers. For these two operators, the methodology for designing fuzzy resolvers with respect to two objective functions was the appropriate choice.

The first part of this thesis deals with studying the effect of the specified bathymetric resolution and ideal bathymetric form parameters on the output from the wave and hydrodynamic modules of Delft-3D. This thesis then describes the use of an optimization to effectively reduce the required bathymetric sampling for input to a numerical forecast model, by using the model’s sensitivity to this input. A genetic algorithm is developed to gradually evolve the survey path for a ship, AUV, or other measurement platform to an optimum, with the resulting effect of the corresponding measured bathymetry on the model, used as a metric. Starting from an initial simulated set of possible random or heuristic sampling paths over the given bathymetry using certain constraints like limited length of track, the algorithm can be used to arrive at the path that would provide the best possible input to the model under those constraints. This suitability is tested by a comparison of the model results obtained by using these new simulated observations, with the results obtained using the best available bathymetry. Two test study areas were considered, and the algorithm was found to consistently converge to a sampling pattern that best captured the bathymetric variability critical to the model prediction.

This research project studies the feasibility of developing and applying an integrated field simulator to simulate the production performance of an entire oil or gas field. It integrates the performance of the reservoir, the wells, the chokes, the gathering system, the surface processing facilities and, whenever applicable, gas and water injection systems. The approach adopted for developing the integrated simulator is to couple existing commercial reservoir and process simulators using available linking technologies. The simulators are dynamically linked and customized into a single hybrid application that benefits from the concept of open software architecture. The integrated field simulator is linked to an optimization routine developed based on the genetic algorithm search strategies. This enables optimization of the system at field level, from the reservoir to the process. Modeling the wells and the gathering network is achieved by customizing the process simulator. This study demonstrates that the integrated simulation improves currentcapabilities to simulate the performance of an entire field and optimize its design. This is achieved by evaluating design options including spread and layout of the wells and gathering system, processing alternatives, reservoir development schemes, and production strategies. Effectiveness of the integrated simulator is demonstrated and tested through several field-level case studies that discuss and investigate technical problems relevant to offshore field development. The case studies cover topics such as process optimization, optimum tie-in of satellite wells into existing process facilities, optimal well location, and field layout assessment of a high pressure high temperature deepwater oil field. Case study results confirm the viability of the total field simulator by demonstrating that the field performance simulation and optimal design were obtained in an automated process with reasonable computation time. No significant simplifying assumptions were required to solve the system and tedious manual data transfer between simulators, as conventionally practiced, was avoided.

University of Macau / Faculty of Science and Technology / Department of Electromechanical Engineering

This research proposes a decision and behavior model which tries to approximate the fund trading. The main idea is based on the principle of the publication ¡§Genetic Algorithms for the Investment of the Mutual Fund with Global Trend Indicator¡¨, and four optimization schemes are proposed as well. First, the calculation of GTI is refined to prevent the possible problems caused by the case that all the fund are getting rise, or the opposite. Second, the tolerance is considered to avoid the reduction of profits owing to the increase of rates for transaction which Funds, those near threshold ones, might exchange ranking too often. Third, the concept of Stop-Loss Point is involved to release the fund dynamically instead of oversell. The last, Someone like to investment more profitable with short-term data, but high-risk. Someone like to investment long-term data, therefore, we added (1-£\)History + (£\)Recent to make users could set by themselves. And we also design genetic algorithm to calculate £\ for reference. Under the constraints of three different coefficients of stop-loss and release, the Return of Investment (ROI) is four times than original one(8.98%), which is compared in 2007.

The first part of this thesis deals with studying the effect of the specified bathymetric resolution and ideal bathymetric form parameters on the output from the wave and hydrodynamic modules of Delft-3D. This thesis then describes the use of an optimization to effectively reduce the required bathymetric sampling for input to a numerical forecast model, by using the model’s sensitivity to this input. A genetic algorithm is developed to gradually evolve the survey path for a ship, AUV, or other measurement platform to an optimum, with the resulting effect of the corresponding measured bathymetry on the model, used as a metric. Starting from an initial simulated set of possible random or heuristic sampling paths over the given bathymetry using certain constraints like limited length of track, the algorithm can be used to arrive at the path that would provide the best possible input to the model under those constraints. This suitability is tested by a comparison of the model results obtained by using these new simulated observations, with the results obtained using the best available bathymetry. Two test study areas were considered, and the algorithm was found to consistently converge to a sampling pattern that best captured the bathymetric variability critical to the model prediction.