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1
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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2
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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3
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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4
Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…This approach was based on fuzzy expert system (FES) using Fuzzy Toolbox of MATLAB software. Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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5
Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025Subjects:Article -
6
A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Finally, an adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order to increase the optimality and stability rates of the proposed path planning algorithm. …”
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7
Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation
Published 2018“…Research has shown that stochastic population-based algorithms such as particle swarm optimization (PSO) can be efficient compared to alternatives for VS-CIT problems. …”
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8
Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms
Published 2011“…All process parameters are selected to conduct the optimization by using some statistical algorithms such as Artificial Neural networks (ANNs), Response Surface Methodology (RSM), Wavelet Neural Network (WNN) and Partial Least Squares (PLS). …”
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A proposed variable parameter control chart for monitoring the multivariate coefficient of variation
Published 2019“…Formulae and algorithms to optimize the various performance measures are discussed. …”
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PID-PSO DC motor position controller design for ankle rehabilitation system
Published 2023“…The transfer function is a model in Matlab software to validate the performance of the control system through simulation compared with real-time experiments. Next, the control algorithms are proposed to design and implement the Proportional-Integral-Derivative (PID) with Particle Swarm Optimization (PSO) controller technique for optimal Proportional (Kp), Integral (Ki) and Derivative (Kd) gains. …”
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11
Online optimal tuning of fuzzy PID controller using grey wolf optimizer for quarter car semi-active suspension system
Published 2024“…To build and improve the Fuzzy PID controller for the semi-active suspension system used in quarter cars, using a novel meta-heuristic technique known as Grey Wolf Optimizer (GWO). Here the magnetorheological damper (MR) fluid with the Fuzzy PID controller was examined to optimize using the GWO algorithm. …”
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Automated calibration of baseline model for energy conservation using multi-objective Evolutionary Programming (EP) / Ahmad Amiruddin Mohammad Aris
Published 2019“…In this regard, three building parameters are taken as decision variables including occupancies, lightings and electrical equipment. …”
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13
Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks
Published 2013“…For real-time applications, simulation results show that RFuzSAHO decision algorithm enhances the VoIP quality (Mean Opinion Score, MOS) up to 5.4% compared to FuzSAHO algorithm when the MS velocity is 20m/s.…”
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14
Ultrasound-assisted process optimization and tribological characteristics of biodiesel from palm-sesame oil via response surface methodology and extreme learning machine - Cuckoo s...
Published 2020“…Extreme learning machine (ELM) and response surface methodology (RSM) techniques were used to model the production process and the input variables (time, catalyst amount, methanol to oil ratio, and duty cycle) were optimized using cuckoo search algorithm. …”
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Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail
Published 2015“…It optimizes random values for network weights and biases. …”
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16
Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…This paper presents the optimization of laser beam machining in additive manufacturing of polymer-based material parameters, specifically focusing on cutting speed, gas pressure of nitrogen, and focal point locations, to achieve optimal mean surface roughness. …”
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A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting
Published 2020“…However, its operation relies on two important parameters (regularization and kernel). Pre-determining the values of parameters will affect the results of the forecasting model; hence, to find the optimal value of these parameters, this study investigates the adaptation of Bat and Cuckoo Search algorithms to optimize LSSVM parameters. …”
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Study of nature inspired computing (NIC) technique for optimal reactive power dispatch problems
Published 2017“…In this research, new nature-inspired meta-heuristic optimization algorithms namely moth-flame optimizer (MFO) and Ant Lion Optimizer (ALO) were implemented to address the optimal reactive power dispatch (ORPD) problems. …”
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19
Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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20
Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links
Published 2022“…Moreover, for the proposed NL-qILMS, we also devised various time-varying techniques for the selection of the optimal q-parameter to improve the performance. Furthermore, the closed-form solutions for the steady-state mean square deviation, excess mean square deviation and mean square error are derived. …”
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