Search Results - (( program selection techniques algorithm ) OR ( java application during algorithm ))
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Multi-floor indoor location estimation system based on wireless local area network
Published 2007“…The most probable match is selected and returned as estimated location based on Bayesian filtering algorithm. …”
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Thesis -
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Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Optimizing tree planting areas through integer programming and improved genetic algorithm
Published 2012“…Therefore, a hybrid algorithm through an incorporation of Integer Programming and Improved Genetic Algorithm was proposed for planting lining design. …”
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Logic Programming In Radial Basis Function Neural Networks
Published 2013“…Two techniques were developed. The first technique is to encode the logic programming in radial basis function neural networks. …”
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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms
Published 2016“…The latest effort to solve this selection problem is the development of the metrics selection model that uses genetic algorithm (GA). …”
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A combined filter line search and trust region method for nonlinear programming
Published 2006“…Computational results on selected large scale CUTE problems on the prototype code fiILS are very encouraging and numerical performance with LOQO and SNOPT show that the algorithm is efficient and reliable.…”
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OPTIMAL LOCATION SELECTION OF SOURCE SUBSTATION OF POWER DISTRIBUTION NETWORK
Published 1999“…A new computer algorithm and program is presented in this paper for optimal location selection od source substation and optimal feeder selection in power distribution network. …”
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Network reconfiguration and control for loss reduction using genetic algorithm
Published 2010“…Note that the 18-bus system is originally without any capacitor. Two selection methods that are used in Genetic Algorithm are the roulette wheel and tournament selections. …”
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Solving unit commitment problem with solar photovoltaic and wind energy generation by using multi-agent evolutionary programming technique / Putri Azimah Salleh
Published 2014“…Several Artificial Intelligence (AI) techniques such as Multi Agent and Evolutionary Programming were combine to produce Multi Agent Evolutionary Programming (MAEP) technique. …”
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Hybrid evolutionary-dolphin echolocation programming for sizing optimization of stand-alone photovoltaic systems / Zulkifli Othman
Published 2021“…Thus, optimization techniques are frequently incorporated in the sizing algorithms for such systems for the purpose of achieving the best solution. …”
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Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun
Published 2000“…In addition, the system is developed using the developing tools that are essential in web applications, namely. web server, database server, system server and web programming tools such as ASP and Visual Basic. In order to develop an intelligent agent, various programming techniques are used in achieving the property of self learning, information retrieval and searching algorithm. …”
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SUDOKU HELPER
Published 2015“…In this paper research, author presents an algorithm to provide a tutorial for any Sudoku player who got stuck during the solving process. …”
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Final Year Project -
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Towards a better feature subset selection approach
Published 2010“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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