Search Results - (( java implication based algorithm ) OR ( using cost learning algorithm ))
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Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling
Published 2025“…However, limited attention has been given to CHFS when considering holistic cost models using efficient algorithms. This paper presents a novel Greedy-Assisted Teaching-Learning-Based Optimization (GTLBO) algorithm for CHFS. …”
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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, the computational and memory cost of the machine learning is mainly affected by the size of the used datasets. …”
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Improved rsync algorithm to minimize communication cost using multi-agent systems for synchronization in multi-learning management systems
Published 2017“…To meet this requirement, a new Multi LMS (MLMS) model using Sharable Content Object Reference Model (SCORM) specifications to share learning materials among different higher learning institutions (HLIs) has been presented. …”
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Financial trading using learning-based approach
Published 2022“…In this work, deep reinforcement learning algorithms were applied to automate the trading process. …”
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Final Year Project / Dissertation / Thesis -
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Software project estimation with machine learning
Published 2021“…This project involves research about software effort estimation using machine learning algorithms. Software cost and effort estimation are crucial parts of software project development. …”
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Water quality monitoring using machine learning and IoT: a review
Published 2024“…The paper explores various ML algorithms, including supervised and unsupervised learning and deep learning, along with their applications, and discusses the use of IoT sensors for real-time monitoring of water quality parameters such as pH, dissolved oxygen, temperature, and turbidity.…”
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Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications
Published 2025“…The algorithm not only aids in estimating the infrastructure cost of the charging lane but also predicts optimal design parameters using trained data. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network
Published 2016“…Simulation results show convergence, learning and adaptability of the RL based algorithms to dynamic environment toward achieving the optimal solutions. …”
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Feedforward neural network for solving particular fractional differential equations
Published 2024“…In the first scheme, a vectorized algorithm and automatic differentiation are implemented to minimize computational costs. …”
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Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks
Published 2021“…Conventionally back-propagation learning algorithm also termed as (BP-MLP) is used. …”
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A new function of stereo matching algorithm based on hybrid convolutional neural network
Published 2022“…The proposed method’s raw matching cost went through the cost aggregation step using the bilateral filter (BF) to improve accuracy. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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