Search Results - (( simulation optimization using algorithm ) OR ( variable selection process algorithm ))
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. © 2017, UK Simulation Society. …”
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2
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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3
Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…A deterministic mutation-based algorithm is introduced to overcome this problem. Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
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4
Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach
Published 2019“…A multi-objective feature selection approach comprises of multi-objective binary-valued backtracking search algorithm (MOBBSA) as an efficient evolutionary search algorithm and ANFIS method is developed in this paper to extract the most influential subsets of input variables with maximum relevancy and minimum redundancy. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
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6
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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Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks
Published 2013“…In the proposed HATSC scheme, the AHP method is uese for criteria weighting, while the TOPSIS method uses for the selection technique based on a multi-criteria decision-making algorithm is proposed. …”
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8
Rainfall prediction using multiple inclusive models and large climate indices
Published 2023Article -
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A Fast Scheduling Algorithm for WDM Optical Networks
Published 2000“…This time complexity can be improved to O(log3 N) by parallel processing using O(M) processors. Two variations of implementation of the scheduling algorithm have been proposed, namely the Variable Frame Size (VFS) and Limited Frame Size (LFS) schemes. …”
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10
Optimization of process parameters for pyrolsis of waste plastics by T method-1
Published 2023text::Final Year Project -
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Green retrofitting of building using BIM-based sustainability optimization
Published 2024“…With the help of BIM tools, which possess advanced algorithms for an effective optimization process, a list of ‘green’ solutions i.e., optimal designs has been generated, out of which the optimal and cost-effective design saved 46% of energy in total. …”
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Green retrofitting of building using BIM-based sustainability optimization
Published 2024“…With the help of BIM tools, which possess advanced algorithms for an effective optimization process, a list of ‘green’ solutions i.e., optimal designs has been generated, out of which the optimal and cost-effective design saved 46% of energy in total. …”
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Rank-based optimal neural network architecture for dissolved oxygen prediction in a 200L bioreactor
Published 2017“…The backpropagation neural network model with Lavenberg Marquardt learning algorithm was developed using 1476 samples real process dataset obtained from a fermentation process in a 200L bioreactor. …”
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14
Fuzzy subtractive clustering (FSC) with exponential membership function for heart failure disease clustering
Published 2022“…It simulated and processed using Fuzzy Subtractive Clustering Algorithm, Jupyter Notebook Software with Python programming language. …”
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Development of robust procedures for partial least square regression with application to near infrared spectral data
Published 2021“…The results indicate that the proposed method outperforms the existing methods in this study. In the in-processing, the PLSR model is very sensitive to the optimal number of PLS components used in the model fitting process. …”
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17
Modeling and Optimization of Tapered Rectangular Thin-walled Columns Subjected to Oblique Loading for Impact Energy Absorption
Published 2013“…The optimal design is obtained by using the constrained nonlinear multivariable optimization algorithm provided by MATLAB. …”
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Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid
Published 2012“…The fault detection algorithm identifies the time and location of each fault. …”
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Model predictive control based on Lyapunov function and near state vector selection of four-leg inverter / Abdul Mannan Dadu
Published 2018“…Due to the evolution of high processing microprocessors, the model predictive control (MPC) has been widely used in power electronic applications. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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