Название: Advanced Soft Computing Techniques in Data Science, IoT and Cloud Computing
Автор: Sujata Dash, Subhendu K. Pani
Издательство: Springer
Серия: Studies in Big Data
Год: 2021
Страниц: 443
Язык: английский
Формат: pdf (true)
Размер: 12.5 MB
The new applications of soft computing can be regarded as an emerging field in computer science, automatic control engineering, medicine, biology application, natural environmental engineering, and pattern recognition. Now the exemplar model for soft computing is the human brain. However, recent advancements in representation soft computing algorithms (fuzzy logic, evolutionary computation, Machine Learning, and probabilistic reasoning) generate a more intelligent and robust system providing a human interpretable, low-cost, approximate solution. Soft computing-based algorithms have demonstrated great performance to a variety of areas including multimedia retrieval, fault tolerance, system modelling, network architecture, Web semantics, Big Data analytics, time series, biomedical and health informatics, etc. Soft computing approaches such as genetic programming (GP), support vector machine–firefly algorithm (SVM-FFA), artificial neural network (ANN), and support vector machine–wavelet (SVM–Wavelet) have emerged as powerful computational models.