Search Results - (( program internalization based algorithm ) OR ( based optimization method algorithm ))
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A hybrid MEP and AIS Algorithm for energy dispatch in power system
Published 2017“…Based on original Meta Heuristic Evolutionary Programming (Meta-EP) method with a consideration on cloning process as in Artificial Immune System (AIS) algorithm together thus identified as New Meta Heuristic Evolutionary Programming algorithm (NMEP). …”
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Successor selection for Ant Colony Optimization technique algorithm / Muhammad Iskandar Isman
Published 2017“…ACO algorithm is the best solution because it included the optimization technique to optimized the result based on the data criteria needs. …”
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A hybrid intelligent algorithm for solving the bilevel programming models
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Optimal Charging Strategy for Plug-in Hybrid Electric Vehicle Using Evolutionary Algorithm
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A hybrid of ant colony optimization, genetic algorithm and flux balance analysis for optimization of succinic acid production in Escherichia coli
Published 2023“…Ant colony optimization (ACO) is a swarm intelligent optimization that is inspired based on the natural foraging behavior of ant colony. …”
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Modeling of static and dynamic components of bio-nanorobotic systems
Published 2012“…In addition, a graph algorithm based on greedy methods is employed to compute a new set of optimal weighted electronic properties of the fullerenes via computing their Minimum Weight Spanning Trees (MWSTs). …”
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A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm
Published 2014“…The approach is based on optimization of selected test case from test suite T. …”
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Grey Wolf Optimizer for Solving Economic Dispatch Problems
Published 2014“…In addition, the three main steps of hunting, searching for prey, encircling prey, and attacking prey, are implemented. The algorithm is then benchmarked on 20 generating units in economic dispatch, and the results are verified by a comparative study with Biogeography-based optimization (BBO), Lambda Iteration method (LI), Hopfield model based approach (HM), Cuckoo Search (CS), Firefly, Artificial Bee Colony (ABC), Neural Networks training by Artificial Bee Colony (ABCNN), Quadratic Programming (QP) and General Algebraic Modeling System (GAMS). …”
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A comprehensive power restoration approach using rule-based method for 11kV distribution network
Published 2008“…This paper presents a restoration algorithm based on a Rule-Based approach. The algorithm is computationally programmed to provide multiple solutions and to recommend the best option of switching for a dispatcher. …”
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The effect of replacement strategies of genetic algorithm in regression test case prioritization of selected test cases
Published 2015“…This study presents an optimized regression test case prioritization of selected test cases for object-oriented software using Genetic algorithm with different replacement strategies. …”
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Regression test case selection & prioritization using dependence graph and genetic algorithm
Published 2014“…The approach is based on optimization of selected test case from dependency analysis of the source codes. …”
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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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Integration of Computer Simulation, Design of Experiments and Particle Swarm Optimization to Optimize the Production Line Efficiency
Published 2016“…The goal of this paper is to optimize the productivity of manufacturing system by integrating computer simulation, design of experiments (DOE) and particle swarm optimization (PSO) algorithm. …”
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Fuzzy subtractive clustering (FSC) with exponential membership function for heart failure disease clustering
Published 2022“…Result: The results showed that the most optimal number of clusters is 3, which are selected based on the largest PC value. …”
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HELM based Reinforcement Learning for Goal Localization
Published 2016“…In this paper, reinforcement learning method was utilized to find optimal series of actions to localize the goal region. …”
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Proceeding Paper -
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Monotone Data Samples Do Not Always Produce Monotone Fuzzy If- Then Rules: Learning with Ad hoc and System Identification Methods
Published 2017“…Our analysis shows that even with multi-attribute monotone data, non-monotone fuzzy If- Then rules can be produced using an ad hoc method. The same observation can be made, empirically, using a system identification method, e.g., a derivative–based optimization method and the genetic algorithm. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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