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Advanced Applications of Artificial Neural Networks in Scientific Research
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Author(s): Dankan Gowda V. (Department of Electronics and Communication Engineering, BMS Institute of Technology and Management, India), Anjali Sandeep Gaikwad (Department of Computer Application, Bharati Vidyapeeth Institute of Management, Kolhapur, India), Pilli Lalitha Kumari (Department of Computer Science Engineering, Malla Reddy Institute of Technology, Secunderabad, India), Erdal Buyukbicakci (Department of Computer Technologies, Sakarya University of Applied Sciences, Turkey)and Sengul Ibrahimoglu (Embedded Software Department, Deka Electronic Company, Istanbul, Turkey)
Copyright: 2025
Pages: 32
Source title:
Expert Artificial Neural Network Applications for Science and Engineering
Source Author(s)/Editor(s): Lingala Syam Sundar (Prince Mohamamd Bin Fahd University, Saudia Arabia), Deepanraj Balakrishnan (Prince Mohammad Bin Fahd University, Saudi Arabia)and Antonio C.M. Sousa (University of Aveiro, Portugal)
DOI: 10.4018/979-8-3693-7250-0.ch001
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Abstract
This chapter is focused on discussing various aspects of the application of Artificial Neural Networks (ANNs) in scientific research with reference to physics, biology, chemistry, engineering, and environmental sciences. ANNs are discussed with the base on the modeling of complicated systems, the handling of massive amounts of data, as well as forecasting in different fields. Among them are CNNs, RNNs, the increasingly popular Transformers depending on the type of data and the type of tasks they are intended for. It also contains the training, the optimization and the performance measures which are the bare minimum indices defining the stability and the efficiency of ANN structures. Additionally, the proposed system is expanded to incorporate other technologies, including IoT and blockchain, while providing future prospects and directions for Explainable AI (XAI) for improved model interpretability.
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