Search Results - (( using optimization learning algorithms ) OR ( data implication based algorithm ))
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…Practical implications In terms of managerial implications, the findings in this research help to frame the adoption of a more advanced analytical approach to forecasting, using a Machine Learning algorithm, in solving a newsvendor problem. …”
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Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network
Published 2020“…Besides that, another limitation that exists in previous researches is the absence of parameter optimization for the classifier. Thus, this paper proposed metaheuristic algorithms such as Particle Swarm Optimization, Ant Colony Algorithm and Harmony Search Algorithm based feature selection to identify the most significant features of skeleton remains. …”
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A hybrid deep learning-based unsupervised anomaly detection in high dimensional data
Published 2022“…Anomaly detection in high dimensional data is a critical research issue with serious implication in the real-world problems. …”
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Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm
Published 2025“…The study employs a hybrid predictive model that combines Big Data technologies, Extract Load Transfer (ELT) processes, rule-based algorithms (RBA), machine learning (ML), and Power BI visualizations. …”
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Prediction of payment method in convenience stores using machine learning
Published 2023“…The Random Forest algorithm was employed due to its robustness in handling complex, high-dimensional data, and its ability to provide reliable predictions. …”
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Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions
Published 2023“…Thus, this proposed system employs a data science-based framework and six highly advanced data-driven Machine learning and Deep learning algorithms: Support Vector Regressor, Auto-Regressive Integrated Moving Average (ARIMA), Facebook Prophet, Unidirectional LSTM, Bidirectional LSTM, Stacked LSTM. …”
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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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Modified word representation vector based scalar weight for contextual text classification
Published 2024“…Overall, this thesis presents five contributions: the proposed modified word vectors algorithm, the new contextual classification dataset named QCoC, the efficient question-type classifier based on the feed-forward neural network algorithm, the potential transferability of the presented work to other domains, and the practical implications of the presented work towards cases where computational resources are limited or costly.…”
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Artificial intelligence (AI) and its application in architecture design: a thematic review
Published 2025“…The analysis identified six primary themes: 1) Architecture and Science, which includes research on complex systems, genetic algorithms, and machine learning;2) Architecture and Construction Management, including the development of frameworks that support decision making; architecture and interior design, which includes work on space-planning optimization and furniture and occupant arrangement;3) Architecture Interior Design; 4) Architecture and Urban; which encompasses attempts to develop tools to help design new cities; architectural engineering, where building performance analysis was the most-common AI application; 5) Architectural Engineering; and 6) Design Education and Training, in which AI appears most promising for advancing problem-based learning. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…Teaching learning-based optimization is one of the widely accepted metaheuristic algorithms inspired by teaching and learning within classrooms. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…Therefore, in this study a new optimized variant of machine learning algorithms is presented. …”
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An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction
Published 2014“…Backpropagation (BP) learning algorithm is the well-known learning technique that trained ANN. …”
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Particle swarm optimization for neural network learning enhancement
Published 2006“…To overcome this problem, Genetic Algorithm (GA) has been used to determine optimal value for BP parameters such as learning rate and momentum rate and also for weight optimization. …”
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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“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm
Published 2024“…This paper investigates the optimization of a CHFS problem using the Teaching Learning-Based Optimization (TLBO) algorithm. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…The MGT algorithm is useful to explore the properties of the Pareto-optimal offers. …”
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Deriving Optimal Operation Rule for Reservoir System Using Enhanced Optimization Algorithms
Published 2025“…This involves their application to various facets of the reservoir operating system, particularly in determining optimal rule curves. This study delves into the exploration of different algorithms, including Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Firefly Algorithm (FA), Invasive Weed Optimization (IWO), Teaching Learning-Based Optimization (TLBO), and Harmony Search (HS). …”
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Training functional link neural network with ant lion optimizer
Published 2020“…This paper proposed the implementation of Ant Lion Algorithm as learning algorithm to train the FLNN for classification tasks. …”
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