Search Results - (( variable optimization based algorithm ) OR ( parameter optimization _ algorithm ))
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Optimization of turning parameters using ant colony optimization
Published 2008“…This project proposed a new optimization technique based on the ant colony algorithm for solving single-pass turning optimization problems. …”
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Undergraduates Project Papers -
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Optimization of hydropower reservoir operation based on hedging policy using Jaya algorithm
Published 2023Article -
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Optimization machining parameters in pocket milling using genetic algorithm and mastercam
Published 2023“…Genetic Algorithm (GA) has been implemented to obtain the optimum parameters. …”
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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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Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi
Published 2018“…In the next step, the parameter identification as an optimization problem is solved by Moth-flame optimization, which is a novel nature-inspired heuristic algorithm. …”
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Optimization of HVAC system energy consumption in a building using artificial neural network and multi-objective genetic algorithm
Published 2023“…Air conditioning; Buildings; Cooling systems; Decision making; Energy conservation; Energy utilization; Genetic algorithms; Multiobjective optimization; Neural networks; Thermal comfort; Annual energy consumption; Building energy consumption; Building parameters; Dedicated outdoor air systems; Multi-objective genetic algorithm; Objective functions; Passive solar design; Radiant cooling; HVAC; air conditioning; artificial neural network; building; cooling; energy use; genetic algorithm; optimization; temperature effect…”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Consequently, the study involved exploiting optimization techniques to enhance the training artificial intelligence algorithm for streamflow forecasting from a gradient-based to a stochastic population-based approach in several aspects, including solution quality, computational effort, and parameter sensitivity on streanflow in Johor, Malaysia. …”
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Thesis -
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm
Published 2024“…Therefore, this article identified various continuous-time Hammerstein models based on an improved Archimedes optimization algorithm (IAOA) to address these concerns. …”
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To study the multi-objective optimization of EDM using genetic algorithm
Published 2013“…In the process of the study, the second- order mathematical model has been create as a fitness function using MATLAB software to generate multi-objective optimization responses using Genetic Algorithms, peak current, pulse-on time, pulse-off time and servo voltage are act as input of parameter setting. …”
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Undergraduates Project Papers -
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Single and Multiple variables control using Tree Physiology Optimization
Published 2017“…In the proposed method, each shoot from each branch search for possible solution in parallel and the fitness is evaluated based on all best values found by branch search. The proposed algorithm is also compared with deterministic gradient-free algorithm: Nelder-Mead simplex (NMS) and another metaheuristic algorithm: Particle Swarm Optimization (PSO). …”
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Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)
Published 2008“…This paper aims to demonstrate the effectiveness of Multi- Objective Genetic Algorithm Optimization and its robust practical application on the automobile engine valve timing where the variation of performance parameters required for finest tuning to obtain the optimal engine performances. …”
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Proceeding Paper -
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Automatic control of flotation process using computer vision
Published 2015“…A froth model correlating the image variables to process variables and a prediction system estimating the metallurgical parameters based on image variables were then developed by using a neural network structure. …”
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A swarm intelligent approach for multi-objective optimization of compact heat exchangers
Published 2023Article -
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Optimization of cnc turning parameters for minimizing temperature rise in aluminum using a genetic algorithm
Published 2024“…In the second optimization process, machining parameters such as cutting speed, feed rate, and depth of cut are optimized using a multi-objective genetic algorithm to concurrently lower temperature rise and surface roughness. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio...
Published 2023“…Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. …”
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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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