Heart Sound Analysis Using MFCC and Time Frequency Distribution by Ismail, Kamarulafizam, Salleh, Sh. Hussain, J., M. Najeb, Arif, A. K., Chowdhury, A.

“…The coefficient obtained from SVD-PCA and MFCC is later used for classification Artificial Neural Network. The results show that the system is able to produce the accuracy up to 90.0% using the TFD and 80.0% using the MFCC. …”
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The design and development of a system for controlling automotive functions using speech recognition by Ahmad, Abd. Manan

“…Apart from the embedded Artificial Neural Network (ANN) based ASR engine, we developed a prototype engine denoted as Support Vector Machine-Dynamic Shifting Window (SVM-DSW) to accommodate speaker independent mode. …”
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An intelligent method to estimate the inertia matrix of a robot arm for active force control using on-line neural network training scheme by Hussein, Shamsul Bahri, Jamaluddin, Hishamuddin, Mailah, Musa

“…This paper presents a new intelligent controller algorithm comprising an on-line multi-layer artificial neural network (ANN) training scheme to estimate the inertia matrix of the robot arm to enhance the performance of the active force control (AFC) scheme. …”
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Depth estimation of inner wall defects by means of infrared thermography by Syed Abu Bakar, Syed Abdul Rahman, Mohd. Mokji, Musa

“…These parameters are the maximum temperature over the defect area (Tmax-def), the average temperature at the right edge of the defect (Tavg-right), the average temperature at the left edge of the defect (Tavg-left), the average temperature at the top edge of the defect (Tavg-top), and the average temperature over the sound area (Tavg-so). Artificial Neural Network (ANN) was trained with these parameters for estimating the defect depth. …”
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Neural network application in the change of reservoir water level stage forecasting by Ashaary, Nur Athirah, Wan Ishak, Wan Hussain, Ku-Mahamud, Ku Ruhana

“…Artificial Neural Network is one of the computational algorithms that can be applied in developing a forecasting model for the change of reservoir water level stage.Forecasting of the change of reservoir water level stage is vital as the change of the reservoir water level can affect the reservoir operator’s decision.The decision of water release is very critical in both flood and drought seasons where the reservoir should maintain high volume of water during less rainfall and enough space for incoming heavy rainfall. …”
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Forecasting the flood stage of a reservoir based on the changes in upstream rainfall pattern by Raja Mohamad, Raja Nurul Mardhiah, Wan Ishak, Wan Hussain

“…In this study, the experiments conducted proved that an Artificial Neural Network is capable of producing an acceptable performance in terms of its accuracy.…”
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Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis by Adnani, Seyedeh Atena

“…A comparison between one variable at a time, Taguchi method and artificial neural network shows that both Taguchi and ANN can reduce the amount of enzyme, amount of molecular sieve, reaction time and molar ratio in solvent based and solvent free system. …”
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An Application of Radial Basis Function Neural Network for Short Term Load Forecasting Solution by Nurul Faezah, Othman, Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…Comparison with artificial neural network (ANN) also given in this paper.…”
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Age Estimation of Asian Using Soft Computing Model Based on Bone Length of Left Hand by Mohd Faaizie, Darmawan, Mohd Zamri, Osman, Kohbalan, Moorthy

“…Two soft computing models are used to develop the estimation models which are Artificial Neural Network (ANN) and Support Vector Machine (SVM). …”
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Determination of bio-diesel engine combustion pressure using neural network based model by Che Wan, Mohd Noor, R., Mamat, Najafi, G., Anuar, Abu Bakar, Samo, Khalid

“…This study focused on developing the prediction model to determine the combustion pressure of diesel engines by employing artificial neural network methods. Input data for training, testing, and validation of the model were obtained from laboratory engine testing. …”
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Enhanced weighted kernel regression with prior knowledge using robot manipulator problem as a case study by Mohd Ibrahim, Shapiai, Zuwairie, Ibrahim, Marzuki, Khalid

“…In general, WKR has proven to be effective when learning from small samples as compared to artificial neural network with back-propagation (ANNBP) and some other techniques. …”
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Comparative analysis in execution of machine learning in breast cancer identification: a review by Ravindran, Nadarajan, Noorazliza, Sulaiman

“…Support Vector Machine (SVM), Naïve Bayes, K-Nearest Neighbour (KNN), Decision Tree, Artificial Neural Network (ANN), and logistic regression are six methods presented in the review. …”
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Development of vision autonomous guided vehicle behaviour using neural network by Husnul ‘Asyiyyah, Mohamad @ Awang

“…This project is motivated by an interest in promoting the use of artificial neural network in manufacturing. Automated guided vehicle (AGV) is used in advanced manufacturing system that can help to reduce cost and increase efficiency. …”
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A new hybrid method based on kalman filter and adaptive neural network for the robustness improvement of fault detection and identification process by Pebrianti, Dwi

“…A representative Artificial Neural Network (ANN) model is designed and used to classify the fault class. …”
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Microsleep Predicting Comparison Between LSTM and ANN Based on the Analysis of Time Series EEG Signal by Hasan, Md Mahmudul, Hossain, Mirza Mahfuj, Norizam, Sulaiman, Khandaker, Sayma

“…This study analyzes time series EEG signals to predict microsleep employing two deep learning models: Long-Short Term Memory (LSTM) and Artificial Neural Network (ANN). The findings show that the ANN model achieves outstanding metrics in microsleep prediction, outperforming the LSTM in key performance metrics. …”
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Artificial Intelligent Approach for Machining Titanium Alloy in a Nonconventional Process by Khan, Md. Ashikur Rahman, M. M., Rahman, K., Kadirgama

“…Artificial neural networks (ANN) are used in distinct researching fields and professions, and are prepared by cooperation of scientists in different fields such as computer engineering, electronic, structure, biology and so many different branches of science. …”
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Neuromorphic computing in Ginzburg-Landau Polariton-Lattice Systems by Opala, Andrzej, Ghosh, Sanjib, Liew, Timothy C. H., Matuszewski, Michał

“…To name a few examples, artificial-neural-network architectures are commonly used for financial forecasting, speech and image recognition, robotics, medicine, and even research. …”
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Parametric studies on the behaviour of FRP-strengthened RC wall subject to near-field blast effects and fragment loading and development of fast running model (FRM) by Fung, Tat Ching, Tan, Kang Hai, Werner Riedel, Yu, Qingjun, Del Linz, Paolo, Li, Gen, Tu, Huan

“…Following this, the results obtained from the mass runs have been analyzed using artificial neural network (ANN) methods to develop FRM (Fast running model). …”
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Deep learning algorithms for classification of financial time series data by Saputra, Kevin

“…RNN is a type of Artificial Neural Network (ANN) where a directed graph formed based on connections between nodes in which a sequence of information may flow. …”
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Brushless synchronous generator turn-to-turn short circuit fault detection using multilayer neural network by Tun, Pyae Phyo, Kumar, Padmanabhan Sampath, Pratama, Ryan Arya, Liu, Shuyong

“…Then, feedforward neural network will be trained, tested and validated whether or not this artificial neural network can classified healthy and different severity inter-turn short circuit levels by using per unit RMS 3 phases current and voltage quantities as well as fundamental and third harmonic components of current and voltage.…”
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