Search Results - ((((regression algorithm) OR (conversion algorithm))) OR (control algorithm))

Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score by Mirza Rizwan, Sajid

“…Further, it focuses on the development of various forms of local risk prediction models and simple heart risk scores using non-laboratory features and machine learning (ML) algorithms. However, the conversion of a complex form of ML algorithms into a simple statistical model is the prime concern. …”
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Model predictive control of bidirectional isolated DC-DC converter for energy conversion system by Akter P., Uddin M., Mekhilef S., Tan N.M.L., Akagi H.

“…Cost functions; DC transformers; Electric load flow; Electric power factor; Energy conversion; Energy transfer; High frequency transformers; HVDC power transmission; MATLAB; Model predictive control; Power control; Predictive control systems; Reactive power; Voltage control; Bidirectional DC-DC converters; Bidirectional isolated dc-dc converter; Energy conversion systems; Full-bridge dc-dc converters; Power conversion systems; Predictive control; Predictive control algorithm; Unity power factor; DC-DC converters…”

Stability augmentation system of active suspension system in electric vehicle conversion: Towards optimal ride comfort performance by Saiful Anuar, Abu Bakar, Ryosuke, Masuda, Hiromu, Hashimoto, Takeshi, Inaba, Hishamuddin, Jamaluddin, Roslan, Abd Rahman, Pakharuddin, Mohd Samin

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Direct power control method of maximum power point tracking (MPPT) algorithm for Pico-Hydrokinetic River Energy Conversion System by Wan Ismail, Ibrahim, Raja Mohd Taufika, Raja Ismail, Mohd Rusllim, Mohamed

“…The design topology consists of the permanent magnet synchronous generator (PMSG), a three-phase bridge rectifier and a DC boost converter. The proposed MPPT algorithm is a combination of modified hill-climbing search algorithm (MHCS) with the current PI-controller. …”
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Model predictive control of bidirectional isolated DC–DC converter for energy conversion system by Akter, P., Uddin, M., Mekhilef, Saad, Tan, N.M.L., Akagi, H.

“…Model predictive control (MPC) is a powerful and emerging control algorithm in the field of power converters and energy conversion systems. …”
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Modular motor driver with torque control for gripping mechanism by How D.N.T., Baharuddin M.Z., Mohideen S.S.K., Sahari K.S.M., Anuar A.

“…In implementing the project, several algorithms were tested to achieve the torque control algorithm requirement including on-off algorithm, P algorithm, PI algorithm, PD algorithm and PID algorithm. …”

Multi-sources model and control algorithm of an energy management system by Hannan, MA, Azidin, FA, Mohamed, Azah

“…This study’s results suggest that the proposed control algorithm provides an efficient and feasible EMS for LEV.…”
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Carbon dioxide reforming of methane over Ni-based catalysts: Modeling the effect of process parameters on greenhouse gasses conversion using supervised machine learning algorithms by Ayodele B.V., Alsaffar M.A., Mustapa S.I., Kanthasamy R., Wongsakulphasatch S., Cheng C.K.

“…Catalysts; Conjugate gradient method; Learning algorithms; Methane; Multilayer neural networks; Multilayers; Sensitivity analysis; Supervised learning; Auto-regressive; Bayesian regularization; CH$-4$; Greenhouse gasse; Multilayers perceptrons; Neural-networks; Nonlinear autoregressive exogenous; Performance; Process parameters; Supervised machine learning; Carbon dioxide…”

Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin by Mohd Yassin, Ahmad Ihsan

“…This thesis proposes the application of a stochastic optimization algorithm called Binary Particle Swarm Optimization algorithm for structure selection of polynomial NARX/NARMA/NARMAX models. …”
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Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach by Bahadar A., Kanthasamy R., Sait H.H., Zwawi M., Algarni M., Ayodele B.V., Cheng C.K., Wei L.J.

“…Biomass; Coal; Complex networks; Errors; Forecasting; Gasification; Hydrogen production; Learning algorithms; Mean square error; Neural networks; Regression analysis; Sensitivity analysis; Support vector machines; Co-gasification; Gaussian process regression; Hydrogen-rich syngas; Machine learning algorithms; Machine-learning; Neural-networks; Process parameters; Regression model; Support vectors machine; Syn gas; Synthesis gas; coal; hydrogen; synfuel; biomass; chemical reaction; detection method; hydrogen; machine learning; multicriteria analysis; algorithm; Article; artificial neural network; biomass; controlled study; gasification; Gaussian processing regression; linear regression analysis; machine learning; mean absolute error; mean square error; parameters; prediction; root mean square error; sensitivity analysis; support vector machine; temperature; Bayes theorem; biomass; Bayes Theorem; Biomass; Coal; Hydrogen; Temperature…”

Artificial intelligent power prediction for efficient resource management of WCDMA mobile network by Tee Y.K., Tinng S.K., Koh J., David Y.

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Fuzzy based BSA optimization for maximum power point tracking controller performance evaluation by Sayem M.A., Nadzirah A., Al-Shetwi A.Q., Hannan M.A., Ker P.J., Rahman S.A., Muttaqi K.M.

“…Computer circuits; Controllers; Conversion efficiency; Fuzzy logic; Learning algorithms; Power control; Solar energy; Solar power generation; Vehicle performance; Algorithms optimizations; Backtracking search algorithms; Controller performance; Fuzzy logic control; Fuzzy logic controllers; Maximum Power Point Tracking; Optimization method; Performances evaluation; Power; Tracking controller; Maximum power point trackers…”

Streamflow Prediction Utilizing Deep Learning and Machine Learning Algorithms for Sustainable Water Supply Management by Latif S.D., Ahmed A.N.

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Predication of entropy generation rate in a concentrating photovoltaic thermal system with twisted tube turbulator using Boosted regression tree algorithm by Wang G., Paw J.K.S., Pasupuleti J., Yaw C.T., Yusaf T., Abdalla A.N., Cai Y.

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A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification by Suihai, Chen, Chih How, Bong, Po Chan, Chiu

“…However, compared with the traditional risk control algorithm (logistic regression algorithm), CatBoost algorithm also needs to have the advantages of high efficiency, low algorithm complexity and strong interpretable ability. …”
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Research On Photovoltaic Mppt Control Method Based On Improved Bas Algorithm And Variable Step-Size Inc Method by Li, Wenli

“…MPPT technology for the PV power system is an effective method to improve the efficacy of PV electricity conversion. Commonly used control methods include CVT method, perturbation and observation method, and incremental conductance method. …”
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An improved maximum power point tracking controller for PV systems using artificial neural network; [Ulepszona metoda ?ledzenia maksymalnej mocy systemu fotowoltaicznego z wykorzys... by Younis M.A., Khatib T., Najeeb M., Mohd Ariffin A.

“…Based on the results; the response of the proposed MPPT controller is faster than the classical P&O algorithm. …”

Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin by Mohd Yassin, Ahmad Ihsan

“…The identification process of NARX/NARMA/NARMAX involves structure selection and parameter estimation, which can be simultaneously performed using the widely accepted Orthogonal Least Squares (OLS) algorithm.…”
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The algorithm is ready to be a Shaykh Murabbi: can we define the social media ethics sometime soon? by Paramboor, Jafar

“…And I do not doubt any more that the algorithm that is engaging with me is going to be a Shaykh Murabbi for myself, being a controller, motivator, and influencer of my consciousness!…”
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Hybrid Genetic Algorithm based Fuzzy Inference System for Data Regression by Wong S.Y., Siah Yap K., Tan C.H.

“…Fuzzy rules; Fuzzy systems; Genetic algorithms; Inference engines; Membership functions; Process control; Regression analysis; Functional relationship; Fuzzy inference systems; Human understanding; Hybrid genetic algorithms; Interpretability; Logical interpretation; Optimization tools; Regression; Fuzzy inference…”