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

“…Subsequently, the integration of embedded correlation-based filtering algorithm has further increased the classification accuracy of training process and testing process by 4.93% and 14.73% 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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Sentiment classification for malay newspaper using clonal selection algorithm / Nur Fitri Nabila Mohamad Nasir by Mohamad Nasir, Nur Fitri Nabila

“…Another objective was to evaluate the proposed model effectiveness in classifying Malay newspaper’s data. In our method, the training of clonal selection algorithm (CSA) is first used to teach algorithm which is intelligent to categorize the sentiment in newspaper’s sentences into the polarity (positive, negative and neutraljfrom the data are collected and the testing was implemented after did the training to test whether a word should be taught correctly or not. …”
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Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector by Wang G., Mukhtar A., Moayedi H., Khalilpoor N., Tt Q.

Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network by Mohd Hamdan, Eleena Yasmeen

“…On the whole, BR algorithm with 60% training and 30 hidden nodes were successfully developed for BOD analysis, meanwhile, 70% training for COD analysis with the regression values of 0.9978 and 0.9976 respectively. …”
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Performance of various training algorithms on scene illumination classification by Hesamian, Mohammad Hesam, Mashohor, Syamsiah, Saripan, M. Iqbal, Wan Adnan, Wan Azizun, Hesamian, B., Hooshyari, M. M.

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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…This knowledge is then converted into computer program or by utilizing exhaustively trained and tested Artificial Intelligence (AI) algorithm. …”
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Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Ramarao, Taj, Mohammed Baloch

“…The developed algorithm is effectively trained, verified and validated with a set of training, dedicated testing and validation data respectively.…”
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Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Rama Rao

“…The developed algorithm is effectively trained, verified and validated with a set of training, dedicated testing and validation data respectively.…”
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Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan by Redzuan, Nur Amalina

“…While in Experiment III used 900 newspaper’s sentences as the training data and 100 newspaper’s sentences as the testing data and the accuracy is unproved to 65.81%. …”
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A Comparative Performance Analysis of ANN Algorithms for MPPT Energy Harvesting in Solar PV System by Roy R.B., Rokonuzzaman M., Amin N., Mishu M.K., Alahakoon S., Rahman S., Mithulananthan N., Rahman K.S., Shakeri M., Pasupuleti J.

A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

“…The focus of the paper is to propose a hybrid approach for the selection of the most influential input variables for the training and testing of neural network based hybrid models. …”
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Jogging activity recognition using k-NN algorithm by Afifah Ismail

“…Finally, usability testing will be used for evaluation. The jogging recognition technology is incorporated into a web-based system using PHP and Python after extraction, training, and test of the data complete, to create the working implementation that can classify the user's jogging activity. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…However, both algorithms tested on MASTER dataset produced different results. …”
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Autoreclosure in extra high voltage lines using taguchi's method and optimized neural networks by K.S.R, Rao, F. D., Zahlay

“…The developed algorithm is effectively trained, verified and validated with a set of training, dedicated testing and validation data respectively. …”
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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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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin by Mohd Shahirudin, Syamir

“…The Windows malware dataset has been trained and tested by these three machine learning algorithms to get the percentage detection accuracy. …”
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Sentiment analysis using negative selection algorithm for Twitter’s messages / Nazirah Che Alhadi by Che Alhadi, Nazirah

“…In order to develop this model classification and prototype, 480 Twitter’s messages were used as training data and 120 Twitter’s messages for testing data to determine the accuracy of the classification model. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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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.

“…Other approaches have been developed to produce robust SDMs, like training data bootstrapping and spatial scale optimisation. …”
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