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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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Thesis -
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Global optimal analysis of variant genetic operations in solar tracking
Published 2023“…Genetic Algorithms (GAs), Evolution Strategies (ES), Evolutionary Programming (EP) and Genetic Programming (GP) are some of the best known types of Evolutionary Algorithm (EA)where it is a class of global search algorithms inspired by natural evolution. …”
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Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…Evolutionary method helps to find the global minima directly without the presence of local minima. …”
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Evolutionary Grammars Based Design Framework For Product Innovation
Published 2012“…Innovation and creativity are the key successful factors and a global priority in engineering industries. This paper describes the development of an evolutionary grammars based design framework for product innovation. …”
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Solving non-convex economic dispatch problem using computational intelligence technique
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The adaptive repository mechanism is a general scheme and can be embedded with high flexibility into any population-based evolutionary algorithm. Moreover, this work is extended to integrate the SPX crossover operator with the adaptive ARDE algorithm in a new way of implementation in order to make the adaptive ARDE algorithm satisfy both the global and local search requirements. …”
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Software testing optimization for large systems using agent-based and NSGA-II algorithms
Published 2023“…The multiobjective optimization problem is addressed in this article using a novel evolutionary technique to find a global solution in the Pareto form. …”
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Optimized processing of satellite signal via evolutionary search algorithm
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Enhanced multi-objective evolutionary mating algorithm with improved crowding distance and levy flight for optimizing comfort index and energy consumption in smart buildings
Published 2025“…This paper introduces a novel Multi-Objective Evolutionary Mating Algorithm (MOEMA) designed to address the inherent challenges of optimizing comfort index and energy consumption in smart building systems. …”
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Adaptive Embedded Clonal Evolutionary Programming (AECEP) for optimal Distributed Generation (DG) location and sizing in a distribution system
Published 2013“…AI methods mainly include Artificial Neural Network (ANN), Expert System (ES), Genetic Algorithm (GA), Evolutionary Programming (EP), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). …”
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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…Evolutionary algorithms have been extensively used to resolve problems associated with multiple and often conflicting objectives. …”
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Feature optimization with metaheuristics for Artificial Neural Network-based chiller power prediction
Published 2025“…This paper presents a novel Evolutionary Mating Algorithm (EMA) hybridized with Artificial Neural Networks (ANN) for optimizing feature selection. …”
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i-Saturate: The New Discovery of Stopping Criterion in Genetic Algorithm
Published 2020“…A stopping criterion for evolutionary algorithms like Genetic Algorithm (GA) is crucial in determining the optimum solution. …”
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Implementation of evolutionary computing models for reference evapotranspiration modeling: Short review, assessment and possible future research directions
Published 2019“…Most recently, advanced machine learning models have been developed for the estimation of ETo. Among several machine learning models, evolutionary computing (EC) has demonstrated a remarkable progression in the modeling of ETo. …”
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