Search Results - (( using normalization _ algorithm ) OR ( using optimization method algorithm ))*
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1
Application of genetic algorithm methods to optimize flowshop sequencing problem
Published 2008“…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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Undergraduates Project Papers -
2
Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025“…Specifically, a normalization-based Binary Bat algorithm is used, where discretization of continuous solution into binary form is performed using a normalization equation. …”
Conference paper -
3
Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…Secondly, this approach hybridizing the FA with the rough algorithm (RA), where RA is used to control the steps of randomness for the FA while optimizing the weights of the standard BPNN model. …”
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Thesis -
4
Optimizing lossless compression by normalized data length in Huffman Algorithm
Published 2022“…The proposed new algorithm has more optimal CR than the various variants of the Huffman-based lossless application. …”
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5
Normal-boundary intersection based parametric multi-objective optimization of green sand mould system
Published 2013“…This method then is used generate optimal solution options to the green sand mould system problem. …”
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Article -
6
Adaptive route optimization for mobile robot navigation using evolutionary algorithm
Published 2021“…For example, Ant Colony Optimization (ACO) is an optimization algorithm based on swarm intelligence which is widely used to solve path planning problem. …”
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Proceedings -
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An algorithmic framework for multiobjective optimization
Published 2013“…Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. …”
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Article -
9
Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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Conference or Workshop Item -
10
Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks
Published 2009“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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Conference or Workshop Item -
11
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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Thesis -
12
Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Thesis -
13
Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with Levenberg Marquardt algorithm to train the ANN and Taguchi's Method to find optimal parameters of the algorithm and number of hidden neurons. …”
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Conference or Workshop Item -
14
Scheduling scientific workflow in multi-cloud: a multi-objective minimum weight optimization decision-making approach
Published 2023“…In particular, we use particle swarm optimization (PSO) to expand the FR-MOS multi-objective scheduling algorithm by using fuzzy resource management to maximize variety and obtain optimal Pareto convergence. …”
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Article -
15
Optimal operation of multi-reservoir systems for increasing power generation using a seagull optimization algorithm and heading policy
Published 2021“…The Seagull Optimization Algorithm was then used to find two heading parameters of the TPHRs. …”
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Article -
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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Thesis -
17
Autoreclosure in extra high voltage lines using taguchi's method and optimized neural networks
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi's Method. …”
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Conference or Workshop Item -
18
Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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Thesis -
19
Low Complexity Error Correction in Low Density Parity Check (LDPC) Code Decoder and Encoder for Decode and Forward Cooperative Wireless Communication
Published 2021“…By using the optimization min-sum belief propagation approach, a low complexity min-sum (MS) based decoding algorithm called Variable Global Optimization Min-Sum (VGOMS) has been developed. …”
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20
A new method for intermediate power point tracking for PV generator under partially shaded conditions in hybrid system
Published 2018“…An optimized control technique for hybrid power generation system is developed in this study to work in both cases with high accuracy and good efficiency, under normal or partially shaded conditions. This technique is based on the combination of two algorithms, the particle swarm optimization algorithm for tracking the global maximum power point, while a newly developed algorithm is used for attaining any other supervisory control set point. …”
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