Search Results - (( control optimization svm algorithm ) OR ( java application sensor algorithm ))

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    Open phase fault-tolerant support vector machine predictive power control for six-phase induction generator WECS by Hamoudi Y., Abdolrasol M.G.M., Amimeur H., Hassaini F., Ker P.J., Ustun T.S.

    Published 2025
    “…Simulation results demonstrate the effectiveness of the OPFT-SVM-PPC control strategy in preserving control over the machine while ensuring high energy quality for the grid with a THD of 2.71%. …”
    Article
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    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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    Improved Direct Torque Control (DTC) Performances Of Induction Machine Using Cascaded H-Bridge Multilevel Inverter by Ramahlingam, Sundram

    Published 2017
    “…The proposed DTC control algorithm can be optimally executed at high computation rate by totally using C-coding with DS1104 controller board. …”
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    Thesis
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    Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

    Published 2024
    “…This study examines the utilization of different Machine Learning algorithms, such as Linear Regression, Decision Trees, Support Vector Machines (SVM), Gradient Boosting, Random Forest, K-Nearest Neighbors (KNN), Convolutional Neural Network (CNN) Regression, and Particle Swarm Optimization (PSO), in the domain of predictive modeling and cost optimization in the field of construction project management. …”
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    Article
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    Malware Classification and Detection using Variations of Machine Learning Algorithm Models by Andi Maslan, Andi Maslan, Abdul Hamid, Abdul Hamid

    Published 2025
    “…While further research requires a special algorithm to improve malware attack detection, in addition to KNN, SVM and Neural Network. …”
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    Modeling and implementation of space vector modulation for three-phase direct torque control matrix converter by Ruzlaini, Ghoni

    Published 2013
    “…In this thesis, the main aim is to improve the performance of the induction motor drive based on the space vector modulation (SVM) method. In addition, some improvement is performed which are by using close-loop induction motor drive controller based on the relations of the efficiency and power factor with the rotor frequency and slip frequency in a steady state mathematical model and second, enhancing this controller by replacing the PI controller with the combination of Direct Torque Control (DTC) and Particle Swarm Optimization (PSO). …”
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    Thesis
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    Real-time Cascading Reservoirs Operation using the Genetic Algorithm and Seasonally Varied Models by DERIB ASFAW, TILAHUN

    Published 2013
    “…Whereas, a seasonally varied model (SVM) has been developed after the analysis of the long-term HA operation data. …”
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    EEG-based emotion recognition using machine learning algorithms by Lam, Yee Wei

    Published 2024
    “…It is because physiological signals are hard to control and more reliable. Thus, this project proposed an optimised machine learning algorithms to classify emotion by analysing brain activity using Electroencephalogram (EEG) signals. …”
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    Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification by Abdul Wahit, Mohamad Aizat

    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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    Reduced torque ripple and switching frequency using optimal DTC switching strategy for open-end winding induction machines by Abd Rahim, Muhd Khairi

    Published 2017
    “…The main benefit of the proposed strategy is its simplicity, where the DTC improvements can be obtained without the common approach, i.e. the use of Space Vector Modulation (SVM) which involves complex control algorithms. …”
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    Human activity recognition via accelerometer and gyro sensors by Tee, Jia Lin

    Published 2023
    “…To implement the data engineering system proposed, two mobile applications, SensorData and SensorDataLogger with user-friendly interfaces and intuitive functionalities are developed using Java programming language and Android Studio. …”
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    Ethereum blockchain-based three factor authentication and multi-contract access control for secure smart home environment in 5G networks by Atiewi S., Al-Rahayfeh A., Almiani M., Abuhussein A., Yussof S.

    Published 2025
    “…The Adaptive Neuro-Fuzzy Inference System (ANFIS) is used for role-based access control and judge contracts. To improve secure service providing, we perform the detection of malicious and vulnerable users using Improved Cuckoo Optimization and Support Vector Machine (ICO-SVM) and Gated Recurrent Unit and Residual Neural Network (GRU-ResNNet) algorithm in ROS-EB which reduces the vulnerability in the smart home. …”
    Article
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    Ensemble learning using multi-objective optimisation for arabic handwritten words by Ghadhban, Haitham Qutaiba

    Published 2021
    “…Multi-Objective Ensemble Oriented (MOEO) formulated to control the classifier topology and provide feedback support for changing the classifiers' topology and weights based on the extension of Non-dominated Sorting Genetic Algorithm (NSGA-II). …”
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    Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation by Rahimizadeh, Hamid

    Published 2009
    “…Comparisons were made between the proposed method to the k-nearest neighbor (KNN) and support vector machine (SVM), methods for image segmentation. Experimental results show that the proposed algorithm works better than other two methods in terms of classifier accuracy with result of more than 99 percent successful segmentation of desired color in varying illumination. …”
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    Thesis