Search Results - (( using optimization sensor algorithm ) OR ( using vectorization learning algorithm ))
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Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset
Published 2020“…However, they have their useful lives and will degrade over time. This issue prompts to be solved using predictive analytics to predict the Remaining Useful Life (RUL) of equipment. …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui
Published 2019“…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. …”
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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“…Finally, the last objective is to improve the optimality of the new approach using a robust Machine Learning strategy. …”
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Smart phone sensor data: Comparative analysis of various classification methods for task of human activity recognition
Published 2018“…Our work has chosen sensor data of six activities such as standing, walking, laying from pre-recorded dataset gathered via smartphone to evaluate the performance of various supervised machine learning algorithms. …”
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Proceedings -
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Web service applications and consumer environments based on ICT-driven optimization
Published 2022“…Therefore, this paper proposes a service recommendation model based on the hybrid embedding of multiple networks and designs a multinetwork hybrid embedding recommendation algorithm. First, the user social relationship network and the user service heterogeneous information network are constructed; then, the embedding vectors of users and services in the same vector space are obtained through multinetwork hybrid embedding learning; finally, the representation vectors of users and services are applied to recommend services to target users. …”
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Drowsiness Detection Using Ocular Indices from EEG Signal
Published 2022“…Different machine learning classification models, including the decision tree, the support vector machine (SVM), the K-nearest neighbor (KNN) method, and the bagged and boosted tree models, were trained based on the seven selected features. …”
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A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar
Published 2007“…In this project, the networks were trained using certain types training algorithm depending on the types of networks; Levenberg Marquardt (LM) for the MLP, competitive network for the LVQ and hybrid learning for ANFIS. …”
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Research Reports -
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Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification
Published 2019“…In this research, the LDA gives as higher as 85.8% of accuracy with six units of the sensors used compared to SVM which is 85% of accuracy percentage with five units of the sensors used. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident
Published 2021“…Thirdly, the pedestrian's behaviour is recognized using grid optimizer in machine learning. Fourthly, four standard vectors for pedestrian walking behaviour are developed. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident
Published 2021“…Thirdly, the pedestrian's behaviour is recognized using grid optimizer in machine learning. Fourthly, four standard vectors for pedestrian walking behaviour are developed. …”
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A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles
Published 2017“…Particle Swarm Optimization has been used in the proposed algorithm to minimize the fitness function. …”
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Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage
Published 2019“…It had been successfully used for optimization of many engineering problems. …”
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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“…For water level prediction, lagged rainfall and water level are used. 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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Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network
Published 2014“…This study proposed Extended Virtual Force and Cuckoo Search (EVFCS) algorithm with a combination of EVFA and CS algorithm to find an optimal node placement. …”
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Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm
Published 2020“…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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Support directional shifting vector: A direction based machine learning classifier
Published 2021“…In this article, we have focused on developing a model of angular nature that performs supervised classification. Here, we have used two shifting vectors named Support Direction Vector (SDV) and Support Origin Vector (SOV) to form a linear function. …”
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Global optimization method for continuous - Time sensor scheduling
Published 2010“…We consider a situation in which several sensors are used to collect data for signal processing since operating multiple sensors simultaneously canses system interference, only one sensor can be active at any one time.The problem of scheduling a discrete-valued optimal control problem.This problem cannot be solved using conventional optimization problem.The Transformed problem is then decomposed into a bi-level optimization problem, which is solved using a discreate filled function method in conjunction with a conventional optimal control algorithm.Numerical results show that our algorithm is robust, efficient, and reliable in attaining a near globally optimal solution.…”
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Provisioning an energy efficient with maximum coverage WSN through biological inspired sensor node placement
Published 2023Conference Paper -
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Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors
Published 2025“…One of the powerful optimization algorithms that is used for feature selection is the Whale Optimization Algorithm (WOA), which is a nature-inspired metaheuristic optimization algorithm that mimics the social behavior of humpback whales. …”
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Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China
Published 2024“…Therefore, this study investigates the capability of various machine learning algorithms in predicting the power production of a reservoir located in China using data from 1979 to 2016. …”
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