Search Results - (( data optimization method algorithm ) OR ( parameters formation based algorithm ))
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A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network
Published 2023“…It evaluates system formation methods, hierarchical structures, and leader selection criteria, comparing various parameters to identify factors influencing node formation and routing. …”
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Integration of knowledge-based seismic inversion and sedimentological investigations for heterogeneous reservoir
Published 2020“…In this study, we present a knowledge based seismic acoustic impedance inversion method which employs rule based method for porosity estimation. …”
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Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian
Published 2009“…By using real time measurements and historical data base, power system state estimator detects errors in measurements and the data base; and calculates an optimal estimate of the system state vector of the bus voltage magnitudes and angles. …”
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4
Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour
Published 2010“…In order to study the effect of data pool formation in training the neural network, two methods have been used to generate the synthetic data. …”
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5
Development and tuning of bacteria foraging optimization algorithm on cell formation in cellular manufacturing system
Published 2013“…This research work inquires the applications of designed experiments aided by multiple regression analysis for tuning of this emerging novel optimization algorithm parameters to the cell formation (CF) problem considering operation sequence. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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Development of cell formation algorithm and model for cellular manufacturing system
Published 2011“…The CMS relies on the principle of grouping machines into machine cells and grouping machine parts into part families that is named cell formation. Cells are formed based on presuming fixed single route and parts demand (traditional cell formation) or fluctuation of parts demand (dynamic cell formation). …”
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Spectrum aware clustering algorithm based on fuzzy logic for sensor based monitoring application / Noorhayati Mohamed Noor …[et al.]
Published 2020“…The cluster heads (CHs) are selected according to the channel availability, residual energy, communication cost and node distribution parameters. Fuzzy logic and weight based techniques combines the four parameters for the CH selection. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…In this study we show how to apply a particular class of optimization methods known as pattern search methods to address these challenges. …”
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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Undergraduates Project Papers -
14
Development of a mathematical model for the prediction of chip formation instability and its verification by fuzzy logic with genetic algorithm
Published 2010“…In this technique, a mathematical model has been developed between the cutting parameters and the instability frequency of the chip serration based on response surface methodology and the model is verified by fuzzy logic with genetic algorithm.…”
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Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant
Published 2022“…Comparative results alongside other existing metaheuristic-based algorithms further confirmed excellence of the proposed method through its superior performance against the slime mould algorithm (SMA), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), grey wolf optimizer (GWO), and safe experimentation dynamics (SED) algorithm.…”
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Conference or Workshop Item -
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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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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
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Data clustering using the bees algorithm
Published 2007“…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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An improved K-nearest neighbour with grasshopper optimization algorithm for imputation of missing data
Published 2021“…Thus, this paper proposes a novel method for imputation of missing data, named KNNGOA, which optimized the KNN imputation technique based on the grasshopper optimization algorithm. …”
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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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