Search Results - (( adaptive two different selection algorithm ) OR ( adaptive a difference evolution algorithm ))*
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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 second taxonomy is a new taxonomy proposed to classify the adaptive DE algorithms in particular into two categories (DE with adaptive parameters and DE with adaptive parameters and strategies) considering the adaptive components used in this algorithm. …”
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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. Post-optimization ANN model was trained using eleven different leaning algorithms. …”
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A comparative study for parameter selection in online auctions
Published 2009“…In this work, three different models of genetic algorithms are considered. …”
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Broadening selection competitive constraint handling algorithm for faster convergence
Published 2020“…The median convergence traces have been compared with two different algorithms based on differential evolution, i:e: Ensemble of Constraint Handling Techniques (ECHT) and Stochastic Ranking Differential Evolution (SRDE). …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…However, the learning complexity of classification is increased due to the expansion number of learning model. Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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Dynamic smart grid communication parameters based cognitive radio network
Published 2023“…The proposed system helps to drive optimal communication parameters to realize power saving, maximum throughput and minimum bit error rate communication modes. A differential evolution algorithm is used to select the optimal transmission parameters for given communication modes based on a fitness function that combines multiple objectives based on appropriate weights. …”
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Backhaul load and performance optimality of partial joint processing schemes in LTE-A networks
Published 2014“…Joint transmission outperforms dynamic point selection but with higher backhaul requirements. The utility of PJP schemes for three different traffic types shows that DPS is preferred over JT for elastic and adaptive applications. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat
Published 2021“…K-Means algorithm a popular efficient clustering techniques and genetic algorithm a widely used evolutionary algorithm and known for its adaptive nature were combined to determine the level of handwriting legibility for each child. …”
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Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…A trend that has emerged recently is to make the algorithm parameters automatically adapt to different problems during optimization, thereby liberating the user from the tedious and time-consuming task of manual setting. …”
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023Conference Paper -
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Performance analysis of hybrid renewable energy systems used for rural electrification in Malaysia / Laith Mahmoud Mohammad Halabi
Published 2017“…Accordingly, the results of predicting monthly global solar radiation showed a very good agreement between the predicted and measured data sets besides it demonstrated the high prediction capability of the developed hybrid models using standalone Adaptive Neuro-Fuzzy Inference System (ANFIS) and hybrid ANFIS models which include ANFIS-PSO (Particle Swarm Optimization), ANFIS-GA (Genetic Algorithm), and ANFIS-DE (Differential Evolution). …”
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Channel quality indicator for long term evolution system based on adaptive threshold feedback compression scheme
Published 2014“…This thesis proposes an adaptive feedback algorithm that uses a threshold scheme to enhance the system throughput while maintaining low Block Error Rate (BLER), Bit Error Rate (BER), and overhead. …”
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Evolution strategy for collaborative beamforming in wireless sensor networks
Published 2013“…Generally, CB uses a group of distributed wireless sensor nodes, which collectively transmit a common message with different proper weights to an intended location. …”
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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio...
Published 2023“…VL-WIDE has accomplished a higher median value for the domination over state-of-the-art algorithms with a higher number of non- dominated solutions value than all other benchmarks. …”
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…The Friedman test result is presented for the performance rank of six benchmark feature selection algorithms and FESSIC algorithm. The Man-Whitney U test is then performed to statistically evaluate the significance difference of the second rank and FESSIC algorithms. …”
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Published 2023“…The evolutionary algorithm has been extensively used to solve a range of combinatorial optimization problems. …”
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Adaptive route optimization for mobile robot navigation using evolutionary algorithm
Published 2021“…However, the performance of ACO is highly dependent on the selection of its parameters. In this paper, the proposed adaptive ACO introduced two different ants, namely abnormal ant and random ant into the normal ACO to increase its global search ability and reduce the high convergence rate of ACO. …”
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A comprehensive comparison of evolutionary optimization limited by number of evaluations against time constraints
Published 2016“…To find out the answer for this question, four well-known and most commonly-used algorithms are tested. Particle swarm optimization (PSO), Differential Evolution (DE), Genetic Algorithms (GA), and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) are tested in three different setups of experiments. …”
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