Search Results - (( using optimization model algorithm ) OR ( using evolution learning algorithm ))
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Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle
Published 2023“…To show the effectiveness of EMA-DL, comparison studies were conducted among other metaheuristic optimizers that were also used to optimize the DL parameters viz, Particles Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE) as well as the Adaptive Moment Estimation (ADAM). …”
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Performances Of Metaheuristic Algorithms In Optimizing Tool Capacity Allocations
Published 2014“…In this research, the algorithms studied includes Genetic Algorithm, Particle Swarm Optimization Algorithm, Differential Evolution Algorithm, Harmony Search Algorithm, Teaching-LearningBased Optimization Algorithm and Black Hole Algorithm. …”
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Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection
Published 2026“…The experiment results show how these algorithms could be used to improve methods for recognizing human activities using wearables technology, such as feature selection, parameter adjustment, and model optimization.…”
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An adaptive HMM based approach for improving e-Learning methods
Published 2023“…This research presents a novel approach to design an e-learning platform with adaptive content delivery. The model proposed in this research is based on clustering of students using K-means algorithm and the course of content delivery is adaptively characterized for each student using Hidden Markov Models. …”
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Nature-Inspired cognitive evolution to play Ms. Pac-Man
Published 2011“…The focus of this research is to explore the hybridization of nature-inspired computation methods for optimization of neural network-based cognition in video games, in this case the combination of a neural network with an evolutionary algorithm. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…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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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer
Published 2025“…The study compares the proposed CNN-LSTM-BMO against other metaheuristic optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Differential Evolution (DE). …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network
Published 2006“…Baldwinian learning uses learning algorithm to change the fitness landscape, but the solution that is found is not encoded back into genetic string. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus
Published 2003“…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. A multilayer feed-forward artificial neural network (ANN) with evolution programming learning algorithm for calculation of voltage stability margins (VSM). …”
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Differential evolution for neural networks learning enhancement
Published 2008“…These algorithms have widely been used to optimize the learning mechanism of classifiers, particularly on Artificial Neural Network (ANN) Classifier. …”
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Broadening selection competitive constraint handling algorithm for faster convergence
Published 2020“…The proposed algorithm has been evaluated using 24 benchmark functions. …”
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The duality of technological innovation and dynamic capabilities: the micro-foundation of China's construction machinery industry's rise up the global value chain
Published 2024“…The study adopts a mixed research method, combining large-scale patent data analysis and in-depth case study, and constructs a longitudinal data set of 146 Chinese construction machinery enterprises from 2005 to 2022. By using structural equation modeling, dynamic panel regression and machine learning algorithms, this study reveals the following main conclusions: (1) The relationship between technological innovation duality and the global value chain position of enterprises is inverted U-shaped, and there is an optimal equilibrium point; (2) Dynamic capabilities partially mediate the relationship between technological innovation duality and global value chain climbing, among which absorptive capacity and reconstruction capacity are particularly critical; (3) The degree of internationalization of enterprises positively moderates the impact of technological innovation duality on dynamic capabilities; (4) The quality of the institutional environment moderates the relationship between technological innovation duality and dynamic capabilities, and a high-quality institutional environment strengthens the positive relationship between the two. …”
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Evolution strategies for evolving artificial neural networks in an arcade game
Published 2010“…The aim of this paper is to use a simple but powerful evolutionary algorithm called Evolution Strategies (ES) to evolve the connection weights and biases of feed-forward artificial neural networks (ANN) and to examine its learning ability through computational experiments in a non-deterministic and dynamic environment, which is the well-known arcade game called Ms. …”
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Modeling 2D appearance evolution for 3D object categorization
Published 2016“…The parameters learned during this process are used as the 3D shape representations. …”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…Instead of solving the original optimal control problem, the model-based optimal control problem is solved. …”
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