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Junhua Wang, Junfei Xu, Yan Lu, Tancheng Xie, Jianjun Peng, Junliang Chen and Yanwei Xu
Laser?arc composite additive manufacturing holds significant potential for a wide range of industrial applications, and the control of morphological dimensions in the deposited layer is a critical aspect of this technology. The width and height dimension...
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Mei-Yan Zhuo, Jinn-Chyi Chen, Ren-Ling Zhang, Yan-Kun Zhan and Wen-Sun Huang
In this study, a seepage prediction model was established for roller-compacted concrete dams using support vector regression (SVR) with hybrid parameter optimization (HPO). The model includes data processing via HPO and machine learning through SVR. HPO ...
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Chongxun Mo, Zhiwei Yan, Rongyong Ma, Xingbi Lei, Yun Deng, Shufeng Lai, Keke Huang and Xixi Mo
As the runoff series exhibit nonlinear and nonstationary characteristics, capturing the embedded periodicity and regularity in the runoff series using a single model is challenging. To account for these runoff characteristics and enhance the forecasting ...
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Muhammad Mateen Yaqoob, Muhammad Nazir, Muhammad Amir Khan, Sajida Qureshi and Amal Al-Rasheed
One of the deadliest diseases, heart disease, claims millions of lives every year worldwide. The biomedical data collected by health service providers (HSPs) contain private information about the patient and are subject to general privacy concerns, and t...
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Annwesha Banerjee Majumder, Somsubhra Gupta, Dharmpal Singh, Biswaranjan Acharya, Vassilis C. Gerogiannis, Andreas Kanavos and Panagiotis Pintelas
Heart disease is a leading global cause of mortality, demanding early detection for effective and timely medical intervention. In this study, we propose a machine learning-based model for early heart disease prediction. This model is trained on a dataset...
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