Search Results - (( using ((function bat) OR (function _)) algorithm ) OR ( based optimization method algorithm ))
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1
Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…The BOGS-BAT algorithm is based on three techniques. The first technique is to move or switch solution from single function to functions that contain more than one objective functions. …”
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2
New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…However, the complexity significantly rises when dealing with multi objective functions. The Modified Adaptive Bats Sonar Algorithm (MABSA), initially designed for single objective optimization and inspired by colony bats' echolocation, has demonstrated efficiency with its simple structure and reduced computation time. …”
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3
Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method
Published 2024Subjects:Conference Paper -
4
A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network
Published 2024“…Methods: It is suggested that the objective function that will be optimized using NMM is the mean squared error of the range of all neighboring anchor nodes installed in the studied WSNs. …”
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5
Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
Published 2018“…Design of hydraulic structures, flood warning systems, evacuation measures, and traffic management require river flood routing. A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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6
Quantum Inspired Computational Intelligence Techniques for Combined Economic Emission Dispatch Problem
Published 2017“…In this research work, we at first separately optimize ELD and emission dispatch problem using particle swarm optimization (PSO), quantum-behaved bat algorithm (QBA) and quantum particle swarm optimization (QPSO) for different number of units. …”
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7
Solving large-scale problems using multi-swarm particle swarm approach
Published 2018“…The results showed that the proposed PSO algorithm outperformed the other algorithms in terms of the optimal solutions and the convergence.…”
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8
A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…To summarise, metaheuristic algorithms can give a superior optimization approach than the traditional artificial neural network method, providing the computing time is within an acceptable range. …”
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9
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. The value of parameter is already set to use when applying every dataset in an experiment. …”
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Undergraduates Project Papers -
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A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
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11
Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy
Published 2014“…To overcome this problem, two successful swarm-intelligence-based global optimization algorithms, cuckoo search (CS) algorithm and wind driven optimization (WDO) for multilevel thresholding using Kapur’s entropy has been employed. …”
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A Preliminary Study on Camera Auto Calibration Problem Using Bat Algorithm
Published 2013“…The cost function used in this paper is based on the Kruppa’s equation. …”
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Optimization of mycelium growth using genetic algorithm for multi-objective functions
Published 2019“…Based on that result, it is concluded that multi-objective optimization problem can be solve using the applied method.…”
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14
Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…The algorithms are evaluated using 30 benchmark functions of the CEC2014 benchmark suite, and then applied to solve PCB drill path optimization case study. …”
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15
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…In the sizing of the SAPV system, the mutation adaptive DE (MADE) algorithm based multi-objective functions minimizes three constraint objective functions. …”
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16
An experimental study of modified black hole algorithms
Published 2018“…The algorithms are evaluated based on unimodal, multimodal, hybrid, and composite functions in CEC2014 benchmark test functions. …”
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17
Hybrid conjugate gradient methods using strong Wolfe line search for Whale Optimization Algorithm / Wan Nur Athirah Wan Mohd Zakirudin
Published 2023“…The nonlinear conjugate gradient (CG) method recently is the most used iterative methods for solving optimizing problems because it requires less storage and easy for implementation. …”
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18
Synthesis of transistor chaining algorithm for CMOS cell layout using euler path / Sukri Hanafiah
Published 1997“…After discussing about the introduction (the basic of CMOS transistor ), we will discuss how to create the Optimal layout of CMOS Functional Array with the minimum separation based on euler path method. …”
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19
An Improved Artificial Immune System Based On Antibody Reminder Method For Mathematical Function Optimization
Published 2010“…The results show that the proposed algorithm is able to improve the conventional CSA in terms of accuracy and stability for single objective functions.…”
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20
Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…Stochastic gradient descent (SGD) is one of the most common algorithms used in solving large unconstrained optimization problems. …”
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