Search Results - (( using (evolutionary OR evolution) bat algorithm ) OR ( basic optimization max algorithm ))
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Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty
Published 2018“…Results showed the volume of water to be released for the future period, based on all evolutionary algorithms used, was less than for the base period, and the bat algorithm with high-reliability index and low vulnerability index performed better among other evolutionary algorithms.…”
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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…The use of the BOGSA algorithm aims to create a new equation for the calculation of the masses of population individuals, as found in the theoretical work in the Strength Pareto Evolutionary Algorithm two (SPEAII) algorithm. …”
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Enhancing benchmark optimization with evolutionary random approach: A comparative analysis of modified adaptive bats sonar algorithm (MABSA)
Published 2025“…This article presents a novel hybrid algorithm, combining the Modified Adaptive Bats Sonar Algorithm (MABSA) with the Squirrel Search Algorithm (SSA), and compares its performance with the original MABSA. …”
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A hybrid bat–swarm algorithm for optimizing dam and reservoir operation
Published 2019“…Recently, evolutionary algorithms (EA) are used to develop optimal operation rules for dam and reservoir water systems. …”
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Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management
Published 2017“…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff
Published 2017“…Basically, the QEEA is based on the Time Domain (TD) and Frequency Domain (FD) scheduling where it is dependent on the QoS requirements to allocate resources. The proposed algorithm is compared against other scheduling algorithms, namely, the Channel and QoS Aware (CQA), Priority Set Scheduler (PSS), Proportional Fair (PF), Maximum Throughput (MT) and Blind Average Throughput (BAT). …”
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Improving neural networks training using experiment design approach
Published 2005“…There are several methods of selecting training data from input space for neural networks which include D-optimal and Max-min design approaches. Consider a function approximation problem (Neural Network using Radial Basic Function structure) and limit the amount of training data, say (m) from N amount of possible data. …”
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Fractal coding of bio-metric image for face authentication
Published 2021“…The thesis also compares the results of enough images of various sizes generated by the proposed algorithms with the results of other fractal coding methods to confirm the algorithms’ clarity, reliability and validity. …”
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