Search Results - (( based classification modeling algorithm ) OR ( using optimization sensor algorithm ))
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Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data
Published 2016“…The developed DT algorithm was applied to object-based classifications in the first study area. …”
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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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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui
Published 2019“…In this study, we have purposed a model named as Optimized Reduced Kernel Extreme Learning Machine (Opt RKELM). …”
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Classification of Agarwood using ANN
Published 2012“…The network developed based on three layers feed forward network and the back propagation learning algorithm was used in executing the network training. …”
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Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm
Published 2019“…The results include flood probabilities and prediction analysis using proposed algorithm.…”
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Proceeding Paper -
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Classification of agarwood using ANN / Muhammad Sharfi Najib ...[et al.]
Published 2012“…The network developed based on three layers feed forward network and the back propagation learning algorithm was used in executing the network training. …”
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Study of hand gesture recognition using impulse radio ultra wideband (IRUWB) radar sensor
Published 2023“…First objective is to determine the optimal setup for IR-UWB radar sensor data acquisition, considering factors such as sensor placement and configuration. …”
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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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Performance evaluation for compression-accuracy trade-off using compressive sensing for EEG-based epileptic seizure detection in wireless tele-monitoring
Published 2013“…DCT is combined with the best basis function neural networks for EEG signals classification.Extensive experimental work is conducted, utilizing four classification models.The obtained results show an improvement in classification accuracies and an optimal classification rate of about 95% is achieved when using NN classifier at 85% of CR in the case of no SNR value.The satisfying results demonstrate the effect of efficient compression on maximizing the sensor lifetime without affecting the application’s accuracy.…”
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Pothole detection using multispectral sensor and unmanned aerial vehicle imagery / Muhammad Hafiz Aizuddin Mohd Zaidi
Published 2024“…The aim of this study is to evaluate the effects of multispectral sensors on pothole detection using very high-resolution images captured by Unmanned Aerial Vehicles (UAVs) based on the structure-from-motion photogrammetry approach. …”
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An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Differing from other complex and difficult classification models, rules-based classification algorithms produce models which are understandable for users. …”
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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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Knowledge base processing method based on text classification algorithm
Published 2023“…The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. …”
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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…The performance of the proposed model was compared with thirteen well-known classification models based on seven datasets. …”
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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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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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Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza
Published 2024“…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. The last objective is to evaluate the accuracy of CNN model in the daisy species classification based on image. …”
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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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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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