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1
Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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Thesis -
2
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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3
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 -
4
Voting algorithms for large scale fault-tolerant systems
Published 2011“…In this research, we proposed optimal algorithms using Divide and Conquer, Brent’s theorem and parallel algorithms, appropriate for today’s large scale systems such as satellite processing systems, traffic control, weather forecasting which all face a large quantity of processing input data. …”
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5
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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6
Profit-based optimal generation scheduling of a microgrid
Published 2023“…The results demonstrate the efficiency of using genetic algorithm to solve the optimization problem. �2010 IEEE.…”
Conference paper -
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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 -
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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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Thesis -
9
Omega grey wolf optimizer (ωGWO) for optimization of overcurrent relays coordination with distributed generation
Published 2019“…The overall protection coordination is thus very complicated and could not be satisfied using the conventional method moreover for the modern distribution system. …”
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10
A new method for intermediate power point tracking for PV generator under partially shaded conditions in hybrid system
Published 2018“…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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11
Genetic algorithm for design optimization of 3-phase semi-conductor rectifier power transformers
Published 2007“…This paper presents the optimal design of a 3-phase rectifier power transformer supplying a dc load by Genetic Algorithm (GA). …”
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12
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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13
Modelling of multi-robot system for search and rescue
Published 2023“…This report focusses on developing a novel multi-robot path planning algorithm based on the Modified Particles Swarm Optimization (MPSO) algorithm for dynamic environments. …”
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Final Year Project / Dissertation / Thesis -
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An efficient IDS using hybrid Magnetic swarm optimization in WANETs
Published 2018“…These features are extracted by tagged index values that represent the information gain out of the training course of the classifier to be used as a base for our developed IDS. In order to improve the accuracy of artificial neural network (ANN) classifier, we have integrated our proposed hybrid magnetic optimization algorithm-particle swarm optimization (MOA-PSO) technique. …”
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15
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Thesis -
16
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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Optimal placement and sizing of distributed generation in radial distribution networks using particle swarm optimization and forward backward sweep method
Published 2012“…The proposed PSO algorithm is used to determine optimal placement and size of DG in radial distribution networks, where Forward Backward Sweep Method (FBSM) of distribution load flow analysis was used, to determine the actual power loss in the system. …”
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18
Optimization of fuzzy rules design using genetic algorithm
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An Efficient IDS Using Hybrid Magnetic Swarm Optimization in WANETs
Published 2018“…These features are extracted by tagged index values that represent the information gain out of the training course of the classifier to be used as a base for our developed IDS. In order to improve the accuracy of artificial neural network (ANN) classifier, we have integrated our proposed hybrid magnetic optimization algorithm-particle swarm optimization (MOA-PSO) technique. …”
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20
Integrating genetic algorithms and fuzzy c-means for anomaly detection
Published 2005“…Fuzzy c-Means allow objects to belong to several clusters simultaneously, with different degrees of membership. Genetic Algorithms (GA) to the problem of selection of optimized feature subsets to reduce the error caused by using land-selected features. …”
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