Search Results - (( variable activation function algorithm ) OR ( evolution identification learning algorithm ))

Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

“…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. …”
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A review on object detection algorithms based deep learning methods / Wan Xing ... [et al.] by Wan Xing, Sultan Mohd, Mohd Rizman, Johari, Juliana, Ahmat Ruslan, Fazlina

“…Deep learning-based object detection algorithms can be categorized into three main types: end-to-end algorithms, two-stage algorithms, and one-stage algorithms. …”
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The exploration of hybrid metaheuristics-based approaches: A bibliometric analysis by Nur Hidayah, Azmidi, Noryanti, Muhammad, Rozieana, Khairuddin

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Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems by Franco, Daniel Jose Da Graca Peceguina

“…Another problematic aspect is related to the intrusion detection solutions that are based on machine learning cluster algorithms to learn systems’ specifications and extract general state-based rules for attacks identification. …”
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Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection by Norfadzlan, Yusup, Izzatul Nabila, Sarbini, Dayang Nurfatimah, Awang Iskandar, Azlan, Mohd Zain, Didik Dwi, Prasetya

“…In the experiment, we conducted an evaluation of the effectiveness and efficiency of four nature-inspired binary algorithms for optimization namely Binary Particle Swarm Optimization (BPSO), Binary Grey Wolf Optimization algorithm (BGWO), Binary Differential Evolution algorithm (BDE), and Binary Salp Swarm algorithm (BSS) - in the context of human activity recognition (HAR). …”
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Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations by Hossain, S.K.S., Ayodele, B.V., Alhulaybi, Z.A., Alwi, M.M.A.

“…The RBFNN model with softmax as the hidden layer activation function and identity as the outer layer activation function has the least predictive performance, as indicated by an R2 of 0.403 and a RMSE of 301.55. …”
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Shunt active power filter using hybrid fuzzy-proportional and crisp-integral control algorithms for total harmonic distortion improvement by Abdul Rahman, Nor Farahaida

“…Utilization of soft-computing algorithms in the operation of Shunt Active Power Filters (SAPFs) becomes a latest trend. …”
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Real time De-mixing system based on LMS adaptive algorithm for blind two source signals separation by Mehrkanoon, S., Moghavvemi, M., Fariborzi, H.

“…The time variant mixing matrix based on random vector with time variable elements are made. Several simulations obtain optimum results of implemented algorithm. …”
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MotionSure: a cloud-based algorithm for detection of injected object in data in motion by Islam, Thouhedul, Olanrewaju, Rashidah Funke, Khalifa, Othman Omran

“…Mostly, the Man In The Middle (MITM) attack happens in this stage by hijacking active session variables, manipulating files and objects. …”
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A novel inertia moment estimation algorithm collaborated with active force control scheme for wheeled mobile robot control in constrained environments by Ali, Mohammed A. H., M. S. A., Radzak, Musa, Mailah, Nukman, Yusoff, Abd Razak, Bushroa, Mohd Sayuti, Ab. Karim, Ameen, Wadea, Jabbar, Waheb A., Alsewari, Abdulrahman A., Rassem, Taha H., Abdullah Nasser, Mohammed Abdullah, Abdulghafor, Rawad

“…The estimation is accomplished by calculating the membership function based on the experts’ views in any form (symmetric or non-symmetric) with lowly or highly overlapped linguistic variables. …”
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A novel inertia moment estimation algorithm collaborated with active force control scheme for wheeled mobile robot control in constrained environments by Ali, Mohammed A. H., Radzak, Muhammad S. A., Mailah, Musa, Yusoff, Nukman, Abd Razak, Bushroa, Ab.Karim, Mohd Sayuti, Ameen, Wadea, Jabbar, Waheb A., Alsewari, Abdulrahman A., Rassem, Taha H., Nasser, Abdullah B., Abdulghafor, Rawad

“…The estimation is accomplished by calculating the membership function based on the experts’ views in any form (symmetric or non-symmetric) with lowly or highly overlapped linguistic variables. …”
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A novel inertia moment estimation algorithm collaborated with active force control scheme for wheeled mobile robot control in constrained environments by Ali, Mohammed A.H., Radzak, Muhammad S.A., Mailah, Musa, Yusoff, Nukman, Abd Razak, Bushroa, Ab. Karim, Mohd Sayuti, Ameen, Wadea, A. Jabbar, Waheb, Alsewari, AbdulRahman A., Rassem, Taha H., Nasser, Abdullah B., Abdulmolla Abdulghafor, Rawad Abdulkhaleq

“…The estimation is accomplished by calculating the membership function based on the experts’ views in any form (symmetric or non-symmetric) with lowly or highly overlapped linguistic variables. …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Forecasting particulate matter concentration using linear and non-linear approaches for air quality decision support by Abdullah S., Ismail M., Ahmed A.N., Abdullah A.M.

Analysis of boiler operational variables prior to tube leakage fault by artificial intelligent system by Al-Kayiem, H.H., Al-Naimi, F.B.I., Amat, W.N.B.W.

“…The results showed that the NN with two hidden layers performed better than one hidden layer using Levenberg-Maquardt training algorithm. Moreover, it was noticed that hyperbolic tangent function for input and output nodes performed better than other activation function types. …”
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Bayesian logistic regression model on risk factors of type 2 diabetes mellitus by Chiaka, Emenyonu Sandra

“…Logistic regression model has long been known and it is commonly used in analysing a binary outcome or dependent variable and connects the binary dependent variable to several independent variables. …”
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Particle swarm optimisation for reactive power compensation on Oman 6 bus electrical grid by Al Mamari, Adnan Saif, Toha, Siti Fauziah, Ahmad, Salmiah, Al Mamari, Ali Salim

“…Reduction of system active power loss is the goal of the function in the projected algorithm. …”
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Depression prediction system from Twitter’s tweet by using sentiment analysis / Nur Amalina Kamaruddin by Kamaruddin, Nur Amalina

“…The classification model was built using Naïve Bayes algorithm. The number of data used in this project is 15952 with 1 independent variable and 1 dependent variables. …”
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Analysis of boiler operational variables prior to tube leakage fault by artificial intelligent system by Al-Kayiem H.H., Al-Naimi F.B.I., Amat W.N.B.W.

“…The results showed that the NN with two hidden layers performed better than one hidden layer using Levenberg-Maquardt training algorithm. Moreover, it was noticed that hyperbolic tangent function for input and output nodes performed better than other activation function types. © 2014 Owned by the authors, published by EDP Sciences.…”