Search Results - (( java implication tree algorithm ) OR ( self regulation method algorithm ))

Novel direct and self-regulating approaches to determine optimum growing multi-experts network structure by Loo, C.K., Rajeswari, M., Rao, M.V.C.

“…However, GMN is not ergonomic due to too many network control parameters. Therefore, a self-regulating GMN (SGMN) algorithm is proposed. …”
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PID Tuning Method Using Chaotic Safe Experimentation Dynamics Algorithm for Elastic Joint Manipulator by Mohd Ikhmil Fadzrizan, Mohd Hanif, Ahmad, Mohd Ashraf, Jui, Julakha Jahan

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Nonlinear dynamic system identification and control via self-regulating modular neural network by Kiong, L.C., Rajeswari, M., Rao, M.V.C.

“…An endeavor is made in this paper to describe a self-regulating constructive multi-model neural network called Self-regulating Growing Multi-Experts Network (SGMN) that can approximate an unknown nonlinear function from observed input-output training data. …”
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Optimal tuning of sigmoid PID controller using nonlinear sine cosine algorithm for the automatic voltage regulator system --- KIV (status in press) by Mohd Helmi, Suid, Mohd Ashraf, Ahmad

“…In addition, the parameters of the proposed SPID controller are obtained using an enhanced self-tuning heuristic optimization method called Nonlinear Sine Cosine Algorithm (NSCA), for achieving a better dynamic response, particularly with regards to the steady-state errors and overshoot of the system. …”
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Performance comparison of feedforward neural network training algorithms in modeling for synthesis of polycaprolactone via biopolymerization by Wong, Yong Jie, Arumugasamy, Senthil Kumar, Jewaratnam, Jegalakshimi

“…This paper compares mean absolute error, mean square error, and mean absolute percentage error (MAPE) in the PCL biopolymerization process for 11 different training algorithms that belong to six classes, namely (1) additive momentum, (2) self-adaptive learning rate, (3) resilient backpropagation, (4) conjugate gradient backpropagation, (5) quasi-Newton, and (6) Bayesian regulation propagation. …”
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Removing mixture of Gaussian and Impulse noise of images using sparse coding by Mahsa Malekzadeh, Saeed Meshgini, Reza Afrouzian, Ali Farzamnia, Sobhan Sheykhivand

“…In this article, we suggest an active weighted approach for mixed noise reduction, defined as Weighted Encoding Sparse Noise Reduction (WESNR), encoded in sparse non-local regulation. The algorithm utilizes a non-local self-similarity feature of image in the sparse coding framework and a pre-learned Principal Component Analysis (PCA) dictionary. …”
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Empowering Energy-Sustainable IoT Devices With Harvest Energy-Optimized Deep Neural Networks by Alzahrani, Saeed, Salh, Adeb, Audah, Lukman, A. Alhartomi, Mohammed, Alotaibi, Abdulaziz, Alsulami, Ruwaybih

“…This paper applied the proposed Optimal Transmit Power and PS Ratio (OTPR) algorithm to maximize the EE for SWIPT based on the partial derivative of Lagrange dual decomposition methods. …”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

“…The explorative and exploitative features of the proposed GA are regulated by substantial crossover probability and mutation rate set up using the Taguchi method. …”
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Prediction of electronic cigarette and vape use among Malaysian: decision tree analysis by Kartiwi, Mira, Ab Rahman, Jamalludin, Nik Mohamed, Mohamad Haniki, Draman, Samsul, Ab Rahman, Norny Syafinaz

“…Methods: The dataset was extracted from the National Electronic Cigarette Survey (NECS) 2016.A total of 4,288 responses were collected. …”
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Performance comparisons between PID and adaptive PID controllers for travel angle control of a bench-top helicopter by Mansor, Hasmah, Mohd Noor, Samsul Bahari, Gunawan, Teddy Surya, Khan, Sheroz, Othman, N. I., Tazali, N., Islam, R. B.

“…Two adaptive algorithms those are pole-placement and deadbeat have been chosen as the method to achieve optimal controller’s parameters. …”
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Performance comparisons between PID and adaptive PID controllers for travel angle control of a bench-top helicopter by Mansor, Hasmah, Mohd Noor, Samsul Bahari, Gunawan, Teddy Surya, Khan, Sheroz, Othman, N. I., Tazali, N., Islam, R. B.

“…Two adaptive algorithms those are pole-placement and deadbeat have been chosen as the method to achieve optimal controller’s parameters. …”
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IRFOC induction motor with rotor time constant estimation modelling and simulation by Radwan, E., Mariun, N., Aris, I., Bash, S. M., Yatim, Abdul Halim Mohamad

“…Purpose– To provide a new and simple inverse rotor time constant identification method which can be used to update an indirect rotor field oriented controlled (IRFOC) induction motor algorithm.Design/methodology/approach– Two different equations are used to estimate the rotor flux in the stator reference frame. …”
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