Results of Parameter Optimisation Using Genetic Algorithms
Parameter optimisation of river water quality models using genetic algorithms
... Table 4.7 shows the statistics of estimated incremental flows for each river reach determined from the 10 events (Table 3.9) to give an overall inchcation of the magnitude of flow used[r] ...
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PID controller optimisation using genetic algorithms
... The Genetic Algorithm did produce reasonably optimal values for the PID parameters; however, the processing time required was prohibitively ...code optimisation techniques could see significant reduction in ...
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Optimisation of Rice Fertiliser Composition using Genetic Algorithms
... Some examples of mixture is blended again into NP and NPK. In rice planting, the right composition of fertilizer is essentially needed. If the composition given is not correct, the growth and quality of rice produced is ...
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Operator and parameter adaptation in genetic algorithms
... are algorithms which encode some parameters for an op- erator into the individual and allow these to evolve, using the updating process itself as the basis for ...The results reported were ...
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Design optimisation of steel portal frames using modified distributed genetic algorithms
... Distributed Genetic Algorithms are input in a form which is shown in ...the optimisation process begins and usually lasts a few minutes depending on the number of design variable and the scale of the ...
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Optimisation of Energy and Exergy of Two-Spool Turbofan Engines using Genetic Algorithms
... The results showed that the combination of energy and exergy efficiencies as the objective function gave significant improvement on the exergy efficiency and specific thrust, although this accompanied by a small ...
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Simulation-Optimisation of a Granularity Controlled Consumer Supply Network Using Genetic Algorithms
... simulation optimisation approach (SOA) within an integrated methodology was ...model, using mixed integer non-linear programming (MINLP) was ...GA optimisation algorithm which simultaneously ...
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The role of mutation in the optimisation of numeric functions by genetic algorithms
... In general the best results are obtained with a coarse granularity; we believe that a fine granularity retards convergence by allowing only small changes in the variabl[r] ...
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Modelling Study Of Supercritical Power Plant And Parameter Identification Using Genetic Algorithms
... simulation results indicated that the model is valid ...accurate results if they are trained with suitable data provided by operating unit ...simulation results show that the model is trustable to ...
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The Applications of Genetic Algorithms in Stock Market Data Mining Optimisation
... 4 Performance evaluations We have tested some stocks of Australia Stock Exchange (ASX). The results are shown in the figure 2 to 5. The Greedy algorithm will cost 10 hours to get the most profit combination, but, ...
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Optimisation of technical rules by genetic algorithms: Evidence from the Madrid stock market*
... rule parameter values are found using a genetic ...The results suggest that, for reasonable trading costs, the technical trading rule is always superior to a risk-adjusted buy-and-hold ...
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Deep learning using genetic algorithms
... of layers, where all neurons in a layer only output to the next layer. This allows all the data to have a specific, non-infinite chain from input to out- put. Various methods exist to train these networks to produce a ...
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Faculty scheduling using genetic algorithms
... a genetic algorithm that could work to solve this program was completed, the fun part of experimenting to make it work bet- ter ...dramatic results, almost un- beaten by any ...
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Genetic Algorithms Using Hadoop MapReduce
... of algorithms like Breadth-First Search, Traveling Salesman problems, Finding Shortest Path problem ...Then using the partitioner for dividing the data parallel in different cluster according to the ...the ...
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Neural Networks using Genetic Algorithms
... In figure 2, crossover site is 7 so after 7th bit the values of parent 1 and parent 2 get interchanged and results as child 1 and child 2. c) Mutation is included, not because the previous process of reproduction ...
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Feature Selection using Genetic Algorithms
... accuracy results can be ...accuracy results occurred by ...the results occurred by ...the results of the T-test comparing the accuracy obtained with different classification models with the ...
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Review for Optimisation of Neural Networks with Genetic Algorithms and Design of Experiments in Stock Market Prediction
... also applied to 40 USA banks from New York Stock Exchange, and a significant difference between methods was observed in the same manner. Istanbul Stock Exchange Index (BIST-100) next day and next week prices were ...
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Structural Topology Optimization Using Genetic Algorithms
... Fig. 3 Design space of the problem The main purpose of this example is to check the feasibility of the proposed ideas. In addition to that, two other purposes of test are performed for this example problem. The first ...
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Optimization Electrical Circuit's Parameter Using Genetic Algorithms (GAs)
... the genetic algorithm is proposed to define appropriate parameters values to meet the desired circuit performance with its ability of parallel searching through the entire solution ...
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Model-based Parameter Optimization of an Engine Control Unit using Genetic Algorithms
... Fitness of each individual in the population is evaluated according to optimization goals. Multiple individuals are stochastically selected from the current population based on their[r] ...
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