Special Issue on INTELLIGENT SENSING, NEURAL COMPUTING AND APPLICATIONS
• 大类 : 工程技术 - 2区
• 小类 : 计算机：人工智能 - 2区
With the rapid development of sensing and computing technologies, the amount of data in the Internet and in our daily life with different forms is experiencing a rapid growth. Cutting-edge technologies are required to deal with these vast and diverse data streams. Generally, we need to solve some challenges, e.g., how to process, analyze or integrate the data, how to extract useful features from data, how to retrieve knowledge from big data, etc, such that we can explore useful information from this data. Computational intelligence, including neural networks, evolutionary computing, fuzzy logic, etc., receives much attention in industrial and academic communities due to its strong ability for data processing.
In recent years, due to the wide success achieved by deep learning models, neural networks have attracted lots of research interest. A set of representative neural network models have been developed, such as radial basis function neural network, wavelet-based hybrid neural networks, deep boltzmann machine, deep auto-encoder, convolutional neural networks, recurrent neural networks, and generative adversarial networks. And these neural network models have been extensively applied to a wide range of fields, e.g., pattern recognition, data mining, decision making, etc. With advances in computing and networking technologies, more complicated and advanced forms of neural networks are expected to emerge, requiring the design of efficient learning algorithms.
The primary purpose of this special issue is to organise a collection of recently developed neural network theories, methodologies and the applications such as classification, multi-source data computing, learning systems, and decision-making activities. The special issue is intended to be an international forum for researchers to report the recent developments in these fields in an original research paper style.