Search Results - (( variable selection techniques algorithm ) OR ( data optimization _ algorithm ))
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1
A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…To address this issue, various data pre-processing methods called Feature Selection (FS) techniques have been presented in the literature. …”
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2
A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant
Published 2023“…These results include providing good solutions as compared to one optimal solution for complex problems. Thus, GA is widely used as feature selection. …”
Conference paper -
3
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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4
Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks
Published 2015“…A hybrid approach that combines ANN and an evolutionary optimization technique, genetic algorithm (GA) is used for the development of a short term load forecast (STLF) model. …”
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5
Integrated ACOR/IACOMV-R-SVM Algorithm
Published 2017“…A direction for ACO is to optimize continuous and mixed (discrete and continuous) variables in solving problems with various types of data. …”
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6
Application of Hybrid Evolutionary Algorithm and thematic map for rule set generation and visualization of chlorophyta abundance at Putrajaya lake / Lau Chia Fong
Published 2013“…This study describes application of a hybrid combination of hybrid evolutionary algorithm (HEA) and thematic map visualization technique in modeling, predicting and visualization of selected algae division growth, Chlorophyta for tropical Putrajaya Lakes and Wetlands (Malaysia). …”
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7
Automated model selection for corporation credit risk assessment using machine learning / Zulkifli Halim
Published 2023“…Hence, the question arises about selecting the optimal model: the characteristic data for CCRA and the best practice machine learning pipelines. …”
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8
Mobile data gathering algorithms for wireless sensor networks
Published 2014“…In this algorithm, the user has to tune an appropriate variable which directly affects the power consumption and the data gathering latency. …”
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9
Initialization procedure in solving Optimal Power Flow (OPF) using Artificial Immune System (AIS) optimization technique / Aimi Idzwan Tajudin
Published 2007“…This project report presents a solution for initializing optimal power flow by using artificial immune system optimization technique. …”
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10
Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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11
Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…The performance of ANNs depend on many factors, including the network structure, the selection of activation function, the learning rate of the training algorithm, and initial synaptic weight values, the number of input variables, and the number of units in the hidden layer. …”
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12
Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…The application of FES optimized by GA on regionalization creates opportunities for further researches which utilizes different types of optimization like Ant Colony Optimization (ACO), ANN’s, Particle Swarm Optimization (PSO) and Imperialist Competitive Algorithm (ICA).…”
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13
Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach
Published 2023“…Looking ahead, future research could explore enhancing DTs' predictive capabilities in athlete selection by incorporating more variables or employing ensemble learning techniques. …”
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14
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…In general, genetic based clustering algorithms showed the ability to reach near global optimal solution. …”
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15
Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…Furthermore, a systematic feature selection approach was proposed in which search algorithms (Ant-Search, Best First-Search and Particle Swamp Optimization (PSO) - Search) performance were evaluated to select the most significant features. …”
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16
Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk
Published 2019“…Meanwhile, based on the fuzzy simulation technique, the model adapted to a series of different distributed fuzzy variable, an improved particle swarm optimization algorithm (IPSO) is used for numerical simulations. …”
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17
Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…Firstly, using MATLAB program, the ANN model is developed based on optimized topology and is then furthered optimized by genetic algorithm (GA) and particle swarm optimization (PSO) using MINITAB program. …”
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18
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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19
Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions
Published 2023“…Moreover, the research experiments are repeated several times to achieve the best results by employing hyperparameter tuning of each algorithm. This involves selecting an appropriate kernel and suitable data normalization technique for SVR, determining ARIMA's (p, d, q) values, and optimizing the loss function values, number of neurons, hidden layers, and epochs in LSTM models. …”
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20
Prediction of lattice constant of pyrochlore compounds using optimized machine learning model
Published 2023“…Our study revealed that, the selected input variables are effectively predicted the lattice constants of pyrochlore compounds. …”
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