Search Results - (( developing function machine algorithm ) OR ( learning object optimization algorithm ))
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Multi-Objective Multi-Exemplar Particle Swarm Optimization Algorithm with Local Awareness
Published 2024“…Many machine learning algorithms excel at handling problems with conflicting objectives. …”
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Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems
Published 2015“…Recently, an online sequential extreme learning machine (OSELM) algorithm has been introduced based on extreme learning machine (ELM) theories for single hidden layer feedforward neural networks (SLFN) and has been applied for different online applications. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…The dissertation aims to develop an effectively decomposed time-series nongradient- based artificial intelligence model for forecasting a time-series regression machine learning task. …”
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Novel reservoir system simulation procedure for gap minimization between water supply and demand
Published 2019“…In this research, an optimization algorithm, namely, the shark machine learning algorithm (SMLA) that has high inertia for obtaining its targets, is proposed that mimics the natural shark process. …”
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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei
Published 2021“…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation
Published 2017“…This would allow the FLC to generate a local path for an obstacle avoidance system unique to mobile robot navigation in dynamic environments. Finally, the last objective is to improve the optimality of the new approach using a robust Machine Learning strategy. …”
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Development of a Neural-Fuzzy Model for Machinability Data Selection in Turning Process
Published 2008“…A neural-fuzzy model has been developed to represent machinability data selection in turning process. …”
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Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification
Published 2019“…The electronic hardware and hand robot structure were integrated to develop an EMG controlled hand robot prototype, and its functionality was tested through three stages: muscular activity detection only, object detection only and the integration of both detection in an algorithm to control the hand robot structure movement to perform opened hand palm and some grasping postures with two trial for each stage. …”
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Analyzing UiTMCTKKT vehicle utilization and travel pattern using predictive analytics
Published 2025“…Two key experiments were conducted using machine learning models. The Experiment 1 focused on classifying vehicle types based on utilization and Experiment 2 involved predicting no of trips per day using classifiers such as Random Forest, Decision Tree, and Support Vector Machine (SVM). …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
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Development Of Generative Computer-Aided Process Planning System For Lathe Machining
Published 2019“…To validate the generated tool-path, G-codes generated in media package file (MPF) file format and verified through CNC lathe machine. Indeed, the developed algorithm was able to determine the minimum unit production cost of lathe machining part model. …”
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Deep reinforcement learning approaches for multi-objective problem in Recommender Systems
Published 2022“…The current major existing multi-objective recommendation approaches utilize collaborative filtering method as rating predictor to replenish the missing ratings and combined with evolutionary algorithm for only bi-objective optimization. …”
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Opposition-based learning simulated kalman filter for Numerical optimization problems
Published 2016“…Simulated Kalman Filter (SKF) optimization algorithm is a population-based optimizer operated mainly based on Kalman filtering. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…There are three objectives in this research. The first objective is to study the effects of varying the architecture designs and parameter values of the backpropagation neural network (BPNN) learning algorithm. …”
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A systematic literature review on the application of artificial intelligence in enhancing care for kidney diseases patients
Published 2024“…AI in healthcare has opened several breakthroughs in healthcare, especially in the management of CKD. Recent developments related to AI, including machine learning, natural language processing, and predictive analytics, have gradually integrated all the stages in CKD care, from early diagnosis to treatment optimization, considering the significantly improved diagnostic accuracy and better patient outcomes. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…This study introduces a novel meta-heuristic optimization algorithm known as quasi-oppositional modified Jaya (QOMJaya) to solve different multi-objective optimal power flow (MOOPF) problems. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…The reason is that, SRT algorithm is sensitive to the accuracy of the learned preferences while MGT algorithm can generate Pareto-optimal offers even with an approximation of the learned preferences.…”
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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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