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Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad
Published 2017“…This thesis proposes data-intensive workflow optimization algorithms. …”
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Thesis -
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost
Published 2024“…PSO-EBGWO is used to optimize the parameters of the CatBoost model. In this method, the Gray Wolf optimized algorithm (EBGWO) is further optimized by particle swarm optimization (PSO), and when combined with it, the convergence performance of the model is improved, the parameters of the model are reduced, and the model is simplified. …”
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Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem
Published 2017“…In this study, we aim to optimize task scheduling and resource utilization using an evolutionary algorithm based on the proposed completion time and monetary cost of cloud service models. …”
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5
Healthcare Data Analysis Using Water Wave Optimization-Based Diagnostic Model
Published 2021“…This paper presents a new diagnostic model for various diseases. In the proposed diagnostic model, a water wave optimization (WWO) algorithm was implemented for improving the diagnosis accuracy. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…DM is optimized using genetic algorithm (GA). GA is a widely used optimization algorithm based on the concept of survival of the fittest. …”
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7
Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This research utilizes a genetic algorithm (GA) to optimize the multi-layer FFNN performance and structure in modelling three datasets: network traffic, rainfall, and tourist. …”
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8
Optimization of attribute selection model using bio-inspired algorithms
Published 2019“…Such a finding indicates that bio-inspired algorithms can contribute in identifying the few most important features to be used in data mining model construction.…”
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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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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Ant colony optimization for rule induction with simulated annealing for terms selection
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Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / M...
Published 2020“…There were 1 optimized model selected from the classification process. …”
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Student Project -
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Long term energy demand forecasting based on hybrid, optimization: Comparative study
Published 2012“…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025Subjects:Article -
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…Secondly, the modeling method of the proposed PV module is validated by experimental data. …”
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16
The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…The proposed algorithm has been compared with the other three famous algorithms, which are Particle Swarm Optimization (PSO), Differential Evolutionary (DE), and Bees Optimization Algorithm (BOA). …”
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Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm
Published 2012“…Despite this success, two problems lessen the use of this technique, these are: non availability of optimal method of estimating model order and the model coefficients determination. …”
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Monograph -
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Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems
Published 2024“…The applications extend beyond established optimization problems, addressing contemporary experiments in control engineering, including Model Order Reduction, Nonlinear System Identification, and Data-driven Control. …”
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An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways
Published 2017“…The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. …”
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