Search Results - adaptive model difference ((evolution algorithm) OR (selection algorithm))
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Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia
Published 2024“…Post-optimization ANN model was trained using eleven different leaning algorithms. …”
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A comparative study for parameter selection in online auctions
Published 2009“…In this work, three different models of genetic algorithms are considered. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…However, the learning complexity of classification is increased due to the expansion number of learning model. Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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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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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
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A Data Mining-Based Model for Assessing Guangzhou's Higher Vocational Colleges 'New Energy Automobile Majors' Vocational Skills
Published 2024“…Along with solving an imbalance in the HVC training market, this study provides an adaptable framework that can be used in different areas of research.…”
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Backhaul load and performance optimality of partial joint processing schemes in LTE-A networks
Published 2014“…Joint transmission outperforms dynamic point selection but with higher backhaul requirements. The utility of PJP schemes for three different traffic types shows that DPS is preferred over JT for elastic and adaptive applications. …”
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Optimized adaptive neuro-fuzzy inference system using metaheuristic algorithms: Application of shield tunnelling ground surface settlement prediction
Published 2021“…The predictive models were various nature-inspired frameworks, such as differential evolution (DE), particle swarm optimization (PSO), genetic algorithm (GA), and ant colony optimizer (ACO) to tune the adaptive neuro-fuzzy inference system (ANFIS). …”
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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Differing from other complex and difficult classification models, rules-based classification algorithms produce models which are understandable for users. …”
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Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction
Published 2024“…However, predicting software defects with irrelevant features and overlapping classes is challenging and can lead to lengthy training and low model accuracy. To address these challenges, this research introduces a novel Depth Linear Discrimination-Oriented Feature Selection Method based on Adaptive Sine Cosine Algorithm, named Depth Adaptive Sine Cosine Feature Selection (DASC-FS). …”
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Performance evaluation of hybrid adaptive neuro-fuzzy inference system models for predicting monthly global solar radiation
Published 2018“…The proposed hybrid models include particle swarm optimization, genetic algorithm and differential evolution. …”
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Speed sensorless control of permanent magnet synchronous motor using model reference adaptive system and artificial neural network / Abdul Mu’iz Nazelan
Published 2019“…Then, the MRAS is modelled and HMLP network is used for its adaptation scheme. …”
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Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network
Published 2016“…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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