Search Results - (( developing relationship model algorithm ) OR ( java implication based algorithm ))
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A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy
Published 2022“…This study uses the genetic algorithm radial basis, neural network model, to make judgments on the relationships contained in this sequence and compare and analyze the prediction effect and generalization ability of the model to verify the applicability of the genetic algorithm radial basis, neural network model, based on the modeling of historical data, which may contain linear and nonlinear relationships by itself, so this study uses the genetic algorithm radial basis, neural network model, to make, compare, and analyze judgments on the relationships contained in this sequence.…”
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Article -
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Rainfall-funoff modelling in batang layar and oya sub-catchments using pre-developed ann model for tinjar catchment
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Final Year Project Report / IMRAD -
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Effort Estimation Model for Function Point Measurement
Published 2007“…This research work has generated an algorithmic effort estimation model for function points measurement. …”
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Thesis -
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M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)
“…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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Monograph -
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Hybrid optimization approach to estimate random demand
Published 2012“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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Conference or Workshop Item -
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Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting
Published 2021“…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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Box-jenkins and genetic algorithm hybrid model for electricity forecasting system
Published 2005“…In this thesis, an approach that combines the Box-Jenkins methodology for SARIMA model and Genetic Algorithm (GA) will been introduced as a new approach in making a forecast. …”
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Development Of An Algorithm To Reduce The Topographical Effects In Reflected Radiance
Published 2020“…To address this problem, we developed algorithms that quantify, reduce, and induce topographical effects in satellite images by exploring the relationship between direct and diffuse solar irradiance. …”
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Laptop price prediction using decision tree algorithm / Nurnazifah Abd Mokti
Published 2024“…This research project focuses on developing a laptop price prediction model using the decision tree algorithm based on laptop specifications. …”
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Ant colony optimization and genetic algorithm models for suspended sediment discharge estimation for gorgan-river, Iran
Published 2011“…Therefore, it is still necessary to develop the model for the discharge-sediment relationship. …”
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Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score
Published 2021“…In developing risk prediction models, two ML algorithms, linear support vector machine and artificial neural network outperformed the existing conventional logistic regression analysis (LRA) model. …”
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Neural network for rainfall runoff modelling
Published 2004“…So, the purpose of this study is to develop a rainfall runoff model for Sungai Tinjar with outlet at Long Jegan, The network was trained using Back Propagation Algorithm.…”
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Final Year Project Report / IMRAD -
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Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…Integration of global search algorithm into ANN model further improved the model performance. …”
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Software for modelling the static and dynamic flux linkage - current characteristics of A 6/4 SRM
Published 1996“…Program in C language was developed to validate the algorithm provided by Torrey [5,7].…”
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Perovskite lattice constant prediction framework using optimized artificial neural network and fuzzy logic models by metaheuristic algorithms
Published 2023“…Although the PSO-Fuzzy model has the best performance of all the compared models, the developed PSO-ANN based model possesses the advantage of easy implementation in addition to its moderate performance.…”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Modified spectral clustering algorithm for semisupervised face annotation modeling
Published 2025“…The research streamlines annotation, reduces manual work, boosts facial recognition performance (98.97% purity), and contributes to computer vision and AI with efficient large-scale face annotation solutions, developing two models.…”
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