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Full-Text Articles in Physical Sciences and Mathematics
Foxann: A Method For Boosting Neural Network Performance, Mahmood A. Jumaah, Yossra H. Ali, Tarik A. Rashid, S. Vimal
Foxann: A Method For Boosting Neural Network Performance, Mahmood A. Jumaah, Yossra H. Ali, Tarik A. Rashid, S. Vimal
Journal of Soft Computing and Computer Applications
Artificial neural networks play a crucial role in machine learning and there is a need to improve their performance. This paper presents FOXANN, a novel classification model that combines the recently developed Fox optimizer with ANN to solve ML problems. Fox optimizer replaces the backpropagation algorithm in ANN; optimizes synaptic weights; and achieves high classification accuracy with a minimum loss, improved model generalization, and interpretability. The performance of FOXANN is evaluated on three standard datasets: Iris Flower, Breast Cancer Wisconsin, and Wine. The results presented in this paper are derived from 100 epochs using 10-fold cross-validation, ensuring that all dataset …
Predicting Open-Pit Mine Production Using Machine Learning Techniques, Faustin Nartey Kumah, Alex Kwasi Saim, Millicent Nkrumah Oppong, Clement Kweku Arthur
Predicting Open-Pit Mine Production Using Machine Learning Techniques, Faustin Nartey Kumah, Alex Kwasi Saim, Millicent Nkrumah Oppong, Clement Kweku Arthur
Journal of Sustainable Mining
In mining, where production is affected by several factors, including equipment availability, it is necessary to develop reliable models to accurately predict mine production to improve operational efficiency. Hence, in this study, four (4) machine learning algorithms – namely: artificial neural network (ANN), random forest (RF), gradient boosting regression (GBR) and decision tree (DT)) – were implemented to predict mine production. Multiple Linear Regression (MLR) analysis was used as a baseline study for comparison purposes. In that regard, one hundred and twenty-six (126) datasets from an open-pit gold mine were used. The developed models were evaluated and compared using the …
Artificial Intelligence-Based Evaluation Of The Factors Affecting The Sales Of An Iron And Steel Company, Mehmet Pekkaya, Zafer Uysal, Aytaç Altan, Seçkin Karasu
Artificial Intelligence-Based Evaluation Of The Factors Affecting The Sales Of An Iron And Steel Company, Mehmet Pekkaya, Zafer Uysal, Aytaç Altan, Seçkin Karasu
Turkish Journal of Electrical Engineering and Computer Sciences
It is important to predict the sales of an iron and steel company and to identify the variables that influence these sales for future planning. The aim in this study was to identify and model the key factors that influence the sales volume of an iron and steel company using artificial neural networks (ANNs). We attempted to obtain an integrated result from the performance/sales levels of 5 models, to use the ANN approach with hybrid algorithms, and also to present an exemplary application in the base metals industry, where there is a limited number of studies. This study contributes to …