Search Results - (( loading classification means algorithm ) OR ( basic optimization sensor algorithm ))
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Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar
Published 2015“…This method will give the best result when clustering the overlapped data in load profile. PNN is a fast training process to do the classification activities. …”
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On Clustering Algorithm Of Coverage Area Problems In Wireless Sensor Networks
Published 2024“…For the proliferation of wireless sensor network, in different environments, an escalation in the lifetime of wireless sensors is mandatory, because among the basic issues concerning WSN is a successful effort to document the coverage of the number of target fields, while maximizing the lifetime of this network. …”
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Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks
Published 2022“…This study developed an optimized variation of the DV-Hop localization algorithm for anisotropic wireless sensor networks. …”
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Efficient transmission based on genetic evolutionary algorithm
Published 2022“…In this paper, an energy-saving mechanism based on genetic algorithm in wireless sensor network (WSN) is proposed. …”
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Proceedings -
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Even-odd scheduling based energy efficient routing for wireless sensor network (WSN) / Muhammad Zafar Iqbal Khan
Published 2022“…Wireless Sensor Network (WSN) is basically composed of battery powered devices which have an obvious limitation of energy on sensors nodes, so it is the foremost motivation to develop a method to save energy of wireless sensor networks where networks are kept alive for a long time. …”
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A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective
Published 2013“…This survey paper is focused on the discussion of best optimal path routing algorithms in wireless sensor networks by using supervised machine learning approaches. …”
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An optimal under frequency load shedding scheme for islanded distribution network / Amalina Izzati Md Isa
Published 2018“…Two new algorithms i.e., Load Classification based Fuzzy Logic (LCFL) and Binary Evolutionary Programming (BEP) are introduced in the module. …”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…The performances obtained show that the optimized APFLC is better than the non-optimize APFLC in terms of RMSE and the settling time.…”
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An application of a novel technique for assessing the operating performance of existing cooling systems on a university campus
Published 2018“…The studied ANFIS-based FCS outperforms the ANFIS-based fuzzy C-means clustering in terms of the regression. Then, the algorithm-based classifier APSO has better results compared to the conventional particle swarm optimization (PSO). …”
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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
Published 2018“…Subsequently,the filtered signal containing useful information was extracted by three methods root mean square (RMS),mean absolute value (MAV),and autoregressive (AR) covariance,all of which are commonly used in TD.A comparative analysis of the three different techniques was performed based on the accuracy performance of the EMG pattern classification using linear vector quantization (LVQ) neural network.In the experimental work undertaken,six healthy subjects comprised of males and females were selected. …”
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A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization
Published 2018“…This project aims to develop a hybrid prediction Model which can target specific corrosion damage mechanisms. The basic ANN Model will be improved by integrating the Particle Swarm Optimization (PSO) algorithm to achieve a better and optimal performance. …”
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A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization
Published 2018“…This project aims to develop a hybrid prediction Model which can target specific corrosion damage mechanisms. The basic ANN Model will be improved by integrating the Particle Swarm Optimization (PSO) algorithm to achieve a better and optimal performance. …”
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A review of navigation systems (integration and algorithms)
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Performance study of the coexistence of Wireless Sensor Networks (WSN) and Wireless Local Area Networks (WLAN) / Muhammad Adib Haron … [et al.]
Published 2008“…To implement WSN integrated with cognitive radio techno 10gy, a new algorithm that provides access mechanism is needed to interactively working with sensor nodes hardware. …”
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Research Reports -
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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…We then consider the task of determining near globally optimal solutions of discrete-valued optimal control problems. …”
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Driver behaviour classification: a research using OBD-II data and machine learning
Published 2024“…The relationship between all features and engine speed is analysed to select the optimal features, which include engine speed, vehicle speed, throttle position, and calculated engine load. Then, the proposed model makes use of the K-Means algorithm to create driving behaviour labels whether belong to safe or aggressive - validated by the safety score criteria. …”
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Development of control algorithm for a new 12s-6p single phase field excited flux switching motor
Published 2020“…For position detection, algorithms merely need a basic infrared transceiver sensor. …”
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Cognitive load assessment through EEG: a dataset from arithmetic and stroop tasks
Published 2025“…This study introduces a thoughtfully curated dataset compris- ing electroencephalogram (EEG) recordings designed to un- ravel mental stress patterns through the perspective of cogni- tive load. The dataset incorporates EEG signals obtained from 15 subjects, with a gender distribution of 8 females and 7 males, and a mean age of 21.5 years [ 1 ]. …”
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Generating an adaptive and robust walking pattern for prosthetic ankle-foot utilizing a nonlinear autoregressive network with exogenous inputs / Hamza Al Kouzbary
Published 2021“…This three-level control structure has at least one element of discrete transition properties that requires many sensors to improve classification accuracy. However, these sensors also lead to higher computational load and costs. …”
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