Search Results - (( control optimization based algorithm ) OR ( using solution learning algorithm ))
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1
Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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2
Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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3
Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers
Published 2022“…OPF is one of the well-known problems in power system operations and with the inclusion of the FACTS devices allocation problems into OPF will make the solution more complex. Thus, seven metaheuristic algorithms: Barnacles Mating Optimizer (BMO), Marine Predators Algorithm (MPA), Moth–Flame Optimization (MFO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching–Learning-Based Optimization (TLBO) and Heap-Based Optimizer (HBO) are used to solve two objective functions: power loss and cost minimizations. …”
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Opposition based Spiral Dynamic Algorithm with an Application to a PID Control of a Flexible Manipulator
Published 2019“…However, the proposed algorithm shows a better control response.…”
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5
Super-opposition spiral dynamic-based fuzzy control for an inverted pendulum system
Published 2022“…An improvement on the spiral dynamic algorithm (SDA), this method uses a concept centered on opposition-based learning, which is used to evaluate the fitness of agents at the opposite location to the current solution. …”
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6
Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…The basic component of the algorithm consists of several clans and each clan searches for the best place (or best solution) based on the position of their leader. …”
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7
Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems
Published 2021“…Another problematic aspect is related to the intrusion detection solutions that are based on machine learning cluster algorithms to learn systems’ specifications and extract general state-based rules for attacks identification. …”
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8
A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites
Published 2019“…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
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9
Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…This enables more controllability of reaching optimal learning without falling into sub-optimality because of over-fitting or under-fitting. …”
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10
CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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11
Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman
Published 2012“…Genetic Algorithm (GA) based learning technique provides an alternative way that involves controlling the learning complexity by adjusting the number of weights of the ANN. …”
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12
A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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13
Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization
Published 2018“…Many meta-heuristic algorithms have been developed to date (e.g. Simulated Annealing (SA), Particle Swarm Optimization (PSO), Teaching Learning based Optimization (TLBO), Grey Wolf Optimizer(GWO) to name a few). …”
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14
A new particle swarm optimization for wireless mesh routing protocol
Published 2008“…The Particle swarm optimization is based on a social-psychological model of social influence and social learning for finding optimal regions of search space in particles population. …”
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15
Cooperative multi agents for intelligent intrusion detection and prevention systems / Shahaboddin Shamshirband
Published 2014“…We investigate the detection capability based on the fuzzy Q-learning (FQL) algorithm and evaluate it using distribute denial of service attacks (DDoS). …”
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16
Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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18
Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function
Published 2019“…The interactive metamodel is extracted using Q-Learning (QL) via online observing and learning of the outflow-inflow traffic characteristics. …”
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19
Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem
Published 2022“…As a multi-agent algorithm, every agent in the population acts as a Kalman filter by using a standard Kalman filter framework, which includes a simulated measurement process and a best-so-far solution as a reference. …”
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20
A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction
Published 2018“…Second, it is to construct on this method to improve an efficient process for prediction problems that can discover efficient solutions at a high speed of convergence. For this purpose, the suggested approach that makes a hybridizing the FA with the robust 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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