Search Results - addition _ (difference OR different) (evolutionary OR evolution) algorithm
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Artificial Neural Controller Synthesis in Autonomous Mobile Cognition
Published 2009“…The Pareto-frontier Differential Evolution (PDE) algorithm is utilized to generate the Pareto optimal sets through a 3-layer feed-forward artificial neural network that optimize the conflicting objectives of robot behavior and network complexity, where the two different types of robot behaviors are phototaxis and RF-localization, respectively. …”
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Artificial Neural Controller Synthesis in Autonomous Mobile Cognition
Published 2009“…The Pareto-frontier Differential Evolution (PDE) algorithm is utilized to generate the Pareto optimal sets through a 3-layer feed-forward artificial neural network that optimize the conflicting objectives of robot behavior and network complexity, where the two different types of robot behaviors are phototaxis and RF-localization, respectively. …”
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A hybrid optimization technique for solving economic emission load dispatch problems
Published 2023text::Final Year Project -
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A novel clustering based genetic algorithm for route optimization
Published 2016“…Genetic Algorithm (GA), a random universal evolutionary search technique that imitates the principle of biological evolution has been applied in solving various problems in different fields of human endeavor. …”
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Evolutionary Fuzzy ARTMAP Neural Networks for Classification of Semiconductor Defects
Published 2014“…In addition, one of the proposed EANNs incorporates a facility to learn overlapping samples of different classes from the imbalanced data environment. …”
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Channel-aware downlink scheduling for quality of service in long term evolution network
Published 2018“…These constraints comprise the use of an inefficient method to determine delay by the buffer size. In the proposed algorithm we, utilize Head of Line delay with channel-related parameters such as user data rate in addition to several pre-defined QoS tunable parameters to formulate a rule that prioritizes different user flows assigned with channel resources in order to improve delay. …”
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Identifying movement of object in multiple images via particle swarm optimization algorithm / Mohd Haidhar Iqbal Hassan
Published 2016“…This project used one of algorithm from category Evolutionary Computing (EC) and that algorithm is Particle Swarm Optimization (PSO). …”
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Impact of genetic operators on energy-efficient wireless sensor network
Published 2019“…The metaheuristic genetic algorithm is an evolutionary algorithm which means that it will always evolve to get an optimum solution. …”
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Proceedings -
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An improved component carrier selection algorithm for downlink long term evolution advanced
Published 2014“…CA is a method that aggregates multiple Component Carriers (CCs) of the same or different frequency bands. Additionally, LTE-A system needs to simultaneously support a mixture of LTE-A and Long Term Evolution (LTE) users. …”
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Proceeding Paper -
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Enhancing solid oxide fuel cell efficiency through advanced model identification using differential evolutionary mutation fennec fox algorithm
Published 2025“…This research introduces a novel approach for optimal SOFC model identification using a differential evolutionary mutation Fennec fox algorithm (DEMFFA). …”
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Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian
Published 2013“…In addition to the normal metrics, the computational time for executing each algorithm was also measured and compared. …”
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Optimized Cover Selection for Audio Steganography Using Multi-Objective Evolutionary Algorithm
Published 2023“…One of the search methods commonly used to find solutions for the trade-off problem in various fields is the Multi-Objective Evolutionary Algorithm (MOEA). Therefore, this research proposed a new method for optimising cover audio selection for audio steganography using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which falls under the MOEA Pareto dominance paradigm. …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…Comparison results of different combinatorial operators, and tests with different probability factors are shown. …”
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Multi-Objective Portfolio Optimization Strategy using the SPEA-II Algorithm
Published 2025“…In addition, the SPEA- II algorithm showed significant efficiency and stability across different frequencies and time periods. …”
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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2024“…The proposed approach is tested and validated on IEEE 57-bus and IEEE 118-bus systems with different case studies. Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”
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Varying Variants For AncDE With MDV Between Target And Trial Vector Measurement
Published 2018“…This paper compares standard Differential Evolution algorithm with AncDE,which adds a separate cache of recent ancestors that serve as an additional source of highquality genetic information.We compare the solutions produced by both DE and AncDE algorithms using benchmarks of 15 different numeric optimisation problems.Two distinct explorations are presented.The first test is distinct algorithmic variants of AncDE.The second part of this paper defines an MDV attribute and results are presented indicating some interesting differences in MDV between the DE and AncDE algorithms.Our findings indicate that ancestors can help to overcome some of the local variations in solutions quality and improve solution quality by improving population diversity.…”
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Evolution strategy for collaborative beamforming in wireless sensor networks
Published 2013“…It becomes a vital problem to achieve CB as the distributed sensor nodes are unaware of their phase relationship. An iterative algorithm using evolution strategy (ES) is proposed to achieve phase alignment at the intended location in static channels, which require one-bit feedback from the receiver destination. …”
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