Search Results - (( using information based algorithm ) OR ( evolution optimization based algorithm ))
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Broadening selection competitive constraint handling algorithm for faster convergence
Published 2020“…The mean closure performance of the BSCCH algorithm is compared against seven selected state-of-the-art algorithms, namely Differential Evolution with Adaptive Trial Vector Generation Strategy and Cluster-replacement-based Feasibility Rule (CACDE), Improved Teaching Learning Based Optimization (ITLBO), Modified Global Best Artificial Bee Colony (MGABC), Stochastic Ranking Differential Evolution (SRDE), Novel Differential Evolution (NDE), Partical Swarm Optimization for solving engineering problems-a new constraint handling mechanism (CVI-PSO) and Ensemble of Constraint Handling Techniques (ECHT). …”
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A refined differential evolution algorithm for improving the performance of optimization process
Published 2011“…DE is developed based on an improved Genetic Algorithm and come with different strategies for faster optimization. …”
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Differential Evolution Based Special Protection and Control Scheme for Contingency Monitoring of Transmission Line Overloading
Published 2017“…In this paper, a Special Protection and Control Scheme (SPCS) based on Differential Evolution (DE) algorithm for optimal generation rescheduling to mitigate line overloads in contingency conditions has been presented. …”
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Differential evolution for neural networks learning enhancement
Published 2008“…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia
Published 2024“…Hybrid model development included the optimization of ANN coefficients (its weights and biases) using adaptive guided differential evolution algorithm. …”
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Differential evolution based special protection and control scheme for contingency monitoring of transmission line overloading
Published 2017“…In this paper, a Special Protection and Control Scheme (SPCS) based on Differential Evolution (DE) algorithm for optimal generation rescheduling to mitigate line overloads in contingency conditions has been presented. …”
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7
Evolution of RF-signal cognition for wheeled mobile robots using pareto multi-objective optimization
Published 2009“…The elitist Pareto-frontier Differential Evolution (PDE) algorithm is used to generate the Pareto optimal set of ANNs that could optimize two objectives in a single run; (1) maximize the mobile robot homing behavior whilst (2) minimize the hidden neurons involved in the feed-forward ANN. …”
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Optimized routing algorithm for mobile multicast source in Wireless Mesh Networks
Published 2015“…Thus this paper proposes a Differential Evolution based optimized mobile multicast routing algorithm for the shared tree architecture. …”
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Proceeding Paper -
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A novel clustering based genetic algorithm for route optimization
Published 2016“…It was also observed that the introduction of clustering based selection algorithm guaranteed the selection of cluster with the optimal solution in every generation. …”
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Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building
Published 2023“…EMA belongs to the evolutionary computation group of nature-inspired metaheuristic algorithms and offers a promising solution. A comparative analysis is conducted with other well-known algorithms such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Ant Colony Optimization (ACO), Biogeography-Based Optimization (BBO), Teaching-Learning Based Optimization (TLBO), and Beluga Whale Optimization (BWO). …”
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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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A filtering algorithm for efficient retrieving of DNA sequence
Published 2009“…The algorithm filtered the expected irrelevant DNA sequences in database from being computed for dynamic programming based optimal alignment process. …”
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A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence
Published 2013“…The Pareto Archived Evolution Strategy (PAES) algorithm is used to generate a Pareto optimal set of ANNs that optimize the conflicting objectives of maximizing game scores and minimizing neural network complexity. …”
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Automated Student Timetable Scheduling System based on Genetic Algorithm
Published 2019“…Genetic algorithm works based on natural evolutions that comprises of several iterations. …”
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Optimization of extractive Automatic Text Summarization using Decomposition-based Multi-objective Differential Evolution and parallelization
Published 2024“…The central challenge in Automatic Text Summarization (ATS) is efficiently generating machine-generated text summaries through optimization algorithms, a critical component for systems dealing with textual information processing. …”
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A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence
Published 2013“…The Pareto Archived Evolution Strategy (PAES) algorithm is used to generate a Pareto optimal set of ANNs that optimize the conflicting objectives of maximizing game scores and minimizing neural network complexity. …”
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Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems
Published 2021“…Another problematic aspect is related to the intrusion detection solutions that are based on machine learning cluster algorithms to learn systems’ specifications and extract general state-based rules for attacks identification. …”
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Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems
Published 2015“…To achieve this objective, an iterative approach based on swarm intelligence is used to find the optimal CQI threshold at which the competing criteria are optimized. …”
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