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Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

“…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

“…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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Advances of metaheuristic algorithms in training neural networks for industrial applications by Chong H.Y., Yap H.J., Tan S.C., Yap K.S., Wong S.Y.

Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

“…The average classification accuracy of 99.47% on the test data achieved the acceptable average success rate. Thus, it can be concluded that the developed algorithm is capable to improve the classification efficiency by improving the generality of the classifier in classifying test data with unpredictable variations under various working conditions.…”
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Object detection system using haar-classifier by Wan Najwa, Wan Ismail

“…Object detection system using Haar-classifier algorithm can perform best performance of high detection rate and high level of accuracy rate.…”
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Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm by Jama, Abdirisaq M., Khalifa, Othman Omran, Subramaniam, Nantha Kumar

“…Proposed real-time training dataset for SVM algorithm achieved highest detection rate of 99.13% while decision tree and Naïve Bayes has 93.28% & 86.41% of attack detection rate, respectively. …”
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Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO) by Ahmed, Ehab Ali

“…Due to that, many algorithms employ different training algorithms to guide the network for providing an accurate result with less training and testing error. …”
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Machine learning algorithms in context of intrusion detection by Mehmood, T., Rais, H.B.Md.

“…Many machine learning techniques have been developed to cope with this problem. These machine learning algorithms develop a detection model in a training phase. …”
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Comparison of feed forward neural network training algorithms for intelligent modeling of dielectric properties of oil palm fruitlets by Adedayo, Ojo O., Mohd Isa, Maryam, Che Soh, Azura, Abbas, Zulkifly

“…In this study, an Artificial Neural Network (ANN) was designed, optimized and deployed to model the dielectric phenomena of microwave interacting with oil palm fruitlets within the frequency range of 2-4GHz. The ANN training data were obtained from Open-ended Coaxial Probe (OCP) microwave measurements and the quasi-static admittance model, the ANN was trained with four different training algorithms: Levenberg Marquardt (LM) algorithm, Gradient Descent with Momentum (GDM) algorithm, Resilient Backpropagation (RP) algorithm and Gradient Descent with Adaptive learning rate (GDA) algorithm. …”
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Target heart rate zone detector during exercise based on real-time facial expression using single shot detection algorithm / Muhammad Azziq Shamsudin, Raihah Aminuddin and Ummu Mar... by Shamsudin, Muhammad Azziq, Aminuddin, Raihah, Abdul Jalil, Ummu Mardhiah

“…Monitoring Target Heart Rate (THR) during exercise is important for the athletes to assess the details of their training. …”
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Performance Measurement on Deep Spiking Neural Network (DSNN) Algorithm in Flood Prediction Environment by Roselind, Tei

“…The results of the study showed that the DSNN algorithm outperformed the other algorithms with a higher ACC rate of 98.10%, an RMSE of 6.5%, a SEN of 93.50%, an SPE rate of 79.00%, and ASP of 89.60%. …”
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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

“…A multilayer feedforward neural network (FFNN) model with 11 different training algorithms is developed for the multivariable nonlinear biopolymerization of polycaprolactone (PCL). …”
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Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu by Sabtu, Melati

“…This project is developed to train the computer programs to recognize objects in the pictures. …”
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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

“…Particularly, GA is utilized to determine the optimal number of hidden layers, number of neurons in each hidden layer, type of training algorithm, type of activation function of hidden and output neurons, initial weight, learning rate, momentum term, and epoch size of a multilayer feed-forward ANN. …”
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Prediction of football club winning rate using Bayesian model algorithm / Adam Khairul Anuar by Khairul Anuar, Adam

“…Objectives involve studying, developing, and evaluating the accuracy of a Bayesian model for predicting winning rates. …”
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Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin by Mohd Nordin, Ahmad Nasreen Aqmal

“…The trained model achieved commendable test accuracy of 97.26% while maintaining a low false alarm rate and miss rate, scoring approximately 3.61% and 2.19% respectively, this result ensuring a robust and efficient approach to R2L intrusion detection. …”
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Hybrid honey badger algorithm with artificial neural network (HBA-ANN) for website phishing detection by Muhammad Arif, Mohamad, Muhammad Aliif, Ahmad, Zuriani, Mustaffa

“…There are multiple techniques in training the network, one of which is training with metaheuristic algorithms. …”
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REDUCING LATENCY IN A VIRTUAL REALITY-BASED TRAINING APPLICATION by P ISKANDAR, YULITA HANUM

“…In order to overcome latency problem, this research is an attempt to suggest a new prediction algorithm based on heuristic that could be used to develop a more effective and general system for virtual training applications. …”
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Optimization of Feeder Bus Routes for Electric Train Service using Ant Colony Algorithm by Yung, Dellon Tan Tzet

“…Nowadays, it has become more and more convenient for the citizens of Malaysia to move around the different states within the country as public transportation such as buses and trains offer affordable rates for their services. …”
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Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

“…To overcome this problem, Genetic Algorithm (GA) has been used to determine optimal value for BP parameters such as learning rate and momentum rate and also for weight optimization. …”
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