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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

“…In this research work, a modified backpropagation neural network is combined with a modified chaos-search genetic algorithm for STLF of one day and a week ahead. Multiple modifications are carried out on the conventional back-propagation (BP) algorithm such as, improvements in the momentum factor and adaptive learning rate. …”
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Characterization of oil palm fruitlets using artificial neural network by Olukayode, Ojo Adedayo

“…To further validate the generalization accuracy of the LSB_ANN, its performance was compared with that of a Multi-ANFIS network as well as those of three different ANN training algorithms: Levenberg Marquardt (LM) algorithm, Resilient Backpropagation (RP) algorithm and Gradient Descent with Adaptive learning rate (GDA). …”
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An initial state of design and development of intelligent knowledge discovery system for stock exchange database by Che Mat @ Mohd Shukor, Zamzarina, Khokhar, Rashid Hafeez, Md Sap, Mohd Noor

“…Generally our clustering algorithm consists of two steps including training and running steps.The training step is conducted for generating the neural network knowledge based on clustering.In running step, neural network knowledge based is used for supporting the Module in order to generate learned complete data, transformed data and interesting clusters that will help to generate interesting rules.…”
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An improved diabetes risk prediction framework : An Indonesian case study by Sutanto, Daniel Hartono

“…Pre-processing resolves the issue of missing data and hence normalizes the data.Outlier treatment employs k-mean clustering to validate the class.Suitable components were selected through comparison of classifier algorithms and feature selection.Attribute weighting based feature selection was selected for assigning weightage.Weighted risk factor was used on training dataset in order to improve accuracy and computation time of the prediction. …”
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Visual analysis to investigate the capability of ANFIS in modelling hydrological relationship using synthetic dataset by Ngahzaifa, Ab. Ghani, Zuriani, Mustaffa, Zafril Rizal, M Azmi

“…In using most of the machine learning algorithms including ANFIS, to obtain the best model, the common and normal approach is always by comparing models of different parameter settings based on the goodness-offit statistical measures. …”
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Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation by Chen, Qipeng, Xiong, Qiaoqiao, Huang, Haisong, Tang, Saihong, Liu, Zhenghong

“…Finally, the concept of model compression is integrated, utilizing scaling factors in the batch normalization (BN) layer, and introducing sparse factors to perform sparse training on the network. …”
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Cognitive knowledge-based model for adaptive feedback: A case in physics / Andrew Thomas Bimba by Andrew Thomas, Bimba

“…In a computer-based learning environment, feedback is considered as one of the most effective factors which influence learning. …”
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The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

“…In this research, a performance analysis based on different activation functions; gradient descent and gradient descent with momentum, for training the BP algorithm with pre-processing techniques was executed. …”
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A proposed approach for diabetes diagnosis using neuro-fuzzy technique by Alasaady, Maher Talal, Mohd Aris, Teh Noranis, Mohd Sharef, Nurfadhlina, Hamdan, Hazlina

“…In the classification stage, ANFIS classifiers were trained using the hybrid learning algorithm of the neural network. …”
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Prediction of breast cancer diagnosis using machine learning in Malaysian women by Mokhtar, Tengku Muhammad Hanis Tengku

“…This project found that there was a strong interest in the application of ML to breast cancer in the last three decades. The three frequently used ML algorithms were deep learning, support vector machine (SVM), and cluster analysis. …”
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Predicting Market Trends : A Stock Prices Forecasting with Artificial Neural Network for Apple Inc. and Microsoft Corp. by Nur Fazliana, Rahim, Farah Liyana, Azizan, Nur’azra Alia Nisa, Zulpakar

“…Hence, this study employs an Artificial Neural Network model as a machine learning algorithm for forecasting stock prices. The model is based on daily stock prices for Apple Inc. and Microsoft Corp. obtained from Yahoo Finance. …”
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Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining by Termedi @ Termiji, Mohammad Izzuan

“…Four different data mining classification algorithms which are Random Forest, PART, J48 and Naive Bayes will be used on the dataset. …”
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A novel normal parameter reduction algorithm of soft sets by Ma, Xiuqin, Norrozila, Sulaiman, Qin, Hongwu, Herawan, Tutut

“…In this paper, we propose a novel normal parameter reduction algorithm of soft sets based on the oriented-parameter sum, which can be carried out without parameter important degree and decision partition. …”
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Enhancement processing time and accuracy training via significant parameters in the batch BP algorithm by Fatma Susilawati, Mohamad, Mumtazimah, Mohamad, Sarhan, AlDuais

“…We created the dynamic learning rate and dynamic momentum factor for increasing the efficiency of the algorithm. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

“…The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar by Ja'afar, Nur Shahirah

“…These algorithms were developed by using prewar shophouses dataset from 2004 until 2018 based on factors of heritage properties. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding by Mahmoud, Omer, Anwar, Farhat, Salami, Momoh Jimoh Emiyoka

“…One of the essential factors that affect the performance of Artificial Neural Networks is the learning algorithm. …”
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JPEG Image Encryption Using Combined Reversed And Normal Direction-Distorted Dc Permutation With Key Scheduling Algorithm-Based Permutation by Abu, Ahmad Zaidee

“…The proposed approach uses a frequency domain combinational framework of coefficients scrambling with Key Scheduling Algorithm based (KSA-based) permutation. This novel algorithm applies coefficients scrambling using Combined-Reverse-and-Normal-Direction (CRND) scanning together with Distorted DC permutation (DDP). …”
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