Search Results - (( parallel optimization sensor algorithm ) OR ( variable generation _ algorithm ))
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1
Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…Stereo vision sensor consists of two stereo cameras, mounted parallel in stationary position. …”
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2
Single-objective and multi-objective optimization algorithms based on sperm fertilization procedure / Hisham Ahmad Theeb Shehadeh
Published 2018“…The obtained results are compared with the results of four algorithms. These algorithms are Genetic Algorithms (GA), Parallel Genetic Algorithm (PGA), Particle Swarm Optimization (PSO) and Accelerated Particle Swarm Optimization (APSO). …”
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Performance monitoring algorithm for optimizing electrical power generated by using photovoltaic system
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4
Adapting the Elitism on the Greedy Algorithm for Variable Strength Combinatorial Test Cases Generation
Published 2018“…This study presented the most recent variable interaction strength (VS) CT strategy using an enhanced variant in the greedy algorithm. …”
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Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique
Published 2023“…In this work, the core size estimation technique of magnetic nanoparticles (MNPs) using the static magnetization curve obtained from a high-Tc SQUID magnetometer and a metaheuristic inversion technique based on the Particle Swarm Optimizer (PSO) algorithm is presented. The high-Tc SQUID magnetometer is constructed from a high-Tc SQUID sensor coupled by a flux transformer to sense the modulated magnetization signal from a sample. …”
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6
Message based random variable length key encryption algorithm.
Published 2009“…Results: Attack on the key generation process was prevented because of random key generation and its dependency to input message. …”
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Optimization of hydropower reservoir operation based on hedging policy using Jaya algorithm
Published 2023“…Ant colony optimization; Hydroelectric power; Hydroelectric power plants; Investments; Particle swarm optimization (PSO); Reservoirs (water); Stream flow; Water supply; Ant colony algorithms; Hydro-power generation; Hydropower reservoirs; Optimization algorithms; Particle swarm optimization algorithm; Reservoir performance; Streamflow generations; Uncertainty and variability; Genetic algorithms…”
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Online teleoperation of writing manipulator through graphics processing unit based accelerated stereo vision
Published 2021“…These algorithms are then parallelized using Compute Unified Device Architecture CUDA C language to run on Graphics Processing Unit GPU for hardware acceleration. …”
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9
Maximizing power generation in variable speed micro-hydro with power point tracking
Published 2022“…As such, this paper aims to explore and develop a feasible maximum power point tracker (MPPT) with perturb and observe (P&O) and genetic algorithm (GA) in providing optimal power generation for variable speed micro-hydro system. …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…Several research efforts have been developed to generate optimal operation rules for dam and reservoir systems utilizing different optimization algorithms. …”
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Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing
Published 2011“…This thesis presents the design and implementation of a new interaction test generation strategy, known as the Particle Swarm-based Test Generator (PSTG), for generating t-way and variable-strength test suites. …”
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12
A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…The lower and upper limit of design variables (0 and 1) were used to find initial material distribution to initialize the firefly algorithm based section of the hybrid algorithm. …”
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13
A variable combinatorial test suite strategy based on modified greedy algorithm
Published 2015“…This proposed will suggest a new CIT strategy based on a modified greedy algorithm (MGA) with addressing the supporting of variable strength interaction to generate a satisfactory test suite size.…”
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Optimal planning of energy storage system for hybrid power system considering multi correlated input stochastic variables
Published 2025“…Also, Cholesky decomposition is adopted to preserve the actual correlation coefficients among the generated input stochastic variables. Moreover, the QMCS method is combined with the probabilistic load flow (PLF) to track the actual output variables. …”
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A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant
Published 2023Subjects:Conference paper -
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A Comparative Analysis of Peak Load Shaving Strategies for Isolated Microgrid Using Actual Data
Published 2022“…The model consists of four major components such as, PV, BESS, variable load, and gas turbine generator (GTG) dispatch models for the proposed algorithm, where the BESS and PV models are not applicable for the capacity addition technique. …”
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Variable step-size hill-climbing search (VS-HCS) MPPT algorithm for hydrokinetic energy harnessing
Published 2025“…In this paper, the Variable-Step Hill Climbing Search (VS-HCS) MPPT algorithm is proposed to solve the limitation of the conventional HCS MPPT. …”
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Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation
Published 2018“…The generation of variable strength test suites is a non-deterministic polynomial-time (NP) hard computational problem \cite{BestounKamalFuzzy2017}. …”
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Book Chapter -
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Application of Hybrid Evolutionary Algorithm and thematic map for rule set generation and visualization of chlorophyta abundance at Putrajaya lake / Lau Chia Fong
Published 2013“…The generated rules are tested with another set data to avoid biasness, which yielded accuracy rate of 73%. …”
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20
Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment
Published 2018“…The results have demonstrated that the categorical and continuous variables of jobs can be used to improve the total execution time and average waiting time of job scheduling algorithms with less overhead in a real environment.…”
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