Search Results - (( using function a algorithm ) OR ( systematic implementation using algorithm ))

Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Y-type Random 2-satisfiability In Discrete Hopfield Neural Network by Guo, Yueling

“…Additionally, the proposed Hybrid Differential Evolution Algorithm was implemented into the training phase to ensure that the cost function of the Discrete Hopfield Neural Network is minimized. …”
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SYSTEMATIC DESIGN OF SIMPLY STRUCTURED COMPENSATOR by FUNG , CHUN TING

“…Effort has been taken by researchers to develop simple and systematic way to design these controllers. This project aims to develop the algorithm for the tuning method that based on Nyquist Stability Criterion and at later stage build a Neural Network Model to predict the tuning parameters for the PID controller. …”
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Modelling Autonomous Evacuation Navigation System (AENS) for optimal route using Dijkstra's algorithm by Abu Samah, Khyrina Airin Fariza

“…Through ST adaptation, all subsystems were integrated and using the “Dijkstra’s algorithm” (DA) by modifying its function from shortest path algorithm to safest and shortest algorithm, to the nearest exit. …”
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

“…On the contrary, the GAANN approach presented here has covered most aspects of multilayer feed-forward ANN in a more comprehensive way. This research focuses on the use of binaryencoded genetic algorithm (GA) to implement efficient search strategies for the optimal architecture and training parameters of a multilayer feed-forward ANN. …”
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Collision avoidance mechanisms using artificial potential field for UAVs by Abdul Azis, Fadilah, Tan, Jie Sim, Md Ghazaly, Mariam, Mohamad Hanif, Noor Hazrin Hany

“…The novelty of this study lies in integrating wind dynamics into the APF model and the systematic use of RMSE as a performance metric across multiple environmental conditions. …”
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Deep learning convolutional neural network algorithms for the early detection and diagnosis of dental caries on periapical radiographs: a systematic review by Musri, Nabila, Christie, Brenda, Ichwan, Solachuddin Jauhari Arief, Cahyanto, Arief

“…Radiography and intraoral images are considered to play a vital role in detecting dental caries; nevertheless, studies have shown that 20% of suspicious areas are mistakenly diagnosed as dental caries using this technique; hence, diagnosis via radiography alone without an objective assessment is inaccurate. …”
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Systematic literature review: Trend analysis on the design of lightweight block cipher by Abdul Alif Zakaria, Azni Hazlizan Ab Halim, Farida Hazwani Mohd Ridzuan, Nur Hafiza Zakaria, Maslina Daud

A controller based on Optimal Type-2 Fuzzy Logic: Systematic design, optimization and real-time implementation by Fayek, H.M., Elamvazuthi, I., Perumal, N., Venkatesh, B.

“…The main scheme is to optimize the gains of the controller using Particle Swarm Optimization (PSO), then optimize only two parameters per type-2 membership function using Genetic Algorithm (GA). …”
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Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

“…The experimentations of the proposed algorithm are conducted using existing benchmark instances and a published case study on an energy-efficient job-shop model. …”
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Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids by Chiaverini, Luca, Macdonald, David W., Hearn, Andrew J., Kaszta, Zaneta, Ash, Eric, Bothwell, Helen M., Can, Ozgun Emre, Channa, Phan, Clements, Gopalasamy Reuben *, Haidir, Iding Achmad, Kyaw, Pyae Phyoe, Moore, Jonathan H., Rasphone, Akchousanh, Tan, Cedric Kai Wei, Cushman, Samuel A.

“…The latter is a machine learning non-parametric algorithm, more tolerant than other approaches in its assumptions, which has often been shown to outperform parametric algorithms. …”
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DurianCare: optimising trunk disease detection and precision farming in a mobile application / Muhammad Haziq Azmi by Azmi, Muhammad Haziq

“…The project will implement automated detection and disease management recommendation algorithms while evaluating the functionality and usability of the designed application. …”
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Empirical analysis and optimization suggestions of Peking Opera audience's use intention of Kuaishou app by Shixia, Yang, Alexander, Chelum

“…The test of the moderating effect finds that Peking Opera exposure experience produces a significant moderating effect in all paths where independent variables influence usage intention, while age only exerts a specific moderating effect in the paths of effort expectancy and algorithm recommendation on usage intention. …”
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Modeling of flood water level prediction using NNARX / Fazlina Ahmat Ruslan by Ahmat Ruslan, Fazlina

“…The pilot plant used as reference process platform in this study is a binary mixture, batch process bubble cap distillation column that suffers from the time-varying nature of its process. …”
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Model input and structure selection in multivariable dynamic modeling of batch distillation column pilot plant / Ilham Rustam by Rustam, Ilham

“…The pilot plant used as reference process platform in this study is a binary mixture, batch process bubble cap distillation column that suffers from the time-varying nature of its process. …”
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