Optimal Control Applications and Methods《最优控制应用与方法》（双月刊）. Optimal Control Applications and Methods will provide a forum for papers on the full range of optimal control and related control design methods. The aim is to encourage new developments in optimal control theory and design methodologies that may lead to advances in real control applications. Papers are encouraged on the development of computational algorithms for solving optimal control and optimization problems.

Optical Switching and Networking《光交换与光网络杂志》（季刊）. Optical Switching and Networking (OSN) is an archival journal aiming to provide complete coverage of all topics of interest to those involved in the optical and high-speed opto-electronic networking areas. The editorial board is committed to providing detailed, constructive feedback to submitted papers, as well as a fast turn-around time.

New Generation Computing《新一代计算》（季刊）. The journal is specially intended to support the development of new computational and cognitive paradigms stemming from the cross-fertilization of various research fields. These fields include, but are not limited to, programming (logic, constraint, functional, object-oriented), distributed/parallel computing, knowledge-based systems, agent-oriented systems, and cognitive aspects of human embodied knowledge. It also encourages theoretical and/or practical papers concerning all types of learning, knowledge discovery, evolutionary mechanisms, human cognition and learning, and emergent systems that can lead to key technologies enabling us to build more complex and intelligent systems.

Neurocomputing《神经计算学》（一年48期）. Neurocomputing publishes articles describing recent fundamental contributions in the field of neurocomputing. Neurocomputing theory, practice and applications are the essential topics being covered.

Neural Processing Letters《神经处理快报》（双月刊）. Neural Processing Letters is an international journal that promotes fast exchange of the current state-of-the art contributions among the artificial neural network community of researchers and users. The Journal publishes technical articles on various aspects of artificial neural networks and machine learning systems. Coverage includes novel architectures, supervised and unsupervised learning algorithms, deep nets, learning theory, network dynamics, self-organization, optimization, biological neural network modelling, and hybrid neural/fuzzy logic/genetic systems.

Neural Networks《神经网络》（月刊）. Neural Networks provides a forum for developing and nurturing an international community of scholars and practitioners who are interested in all aspects of neural networks, including deep learning and related approaches to artificial intelligence and machine learning. Neural Networks welcomes submissions that contribute to the full range of neural networks research, from cognitive modeling and computational neuroscience, through deep neural networks and mathematical analyses, to engineering and technological applications of systems that significantly use neural network concepts and learning techniques.

Neural Network World《神经网络世界》（双月刊）. Neural Network World is a bimonthly open access journal providing the latest developments in the field of informatics with attention mainly devoted to the problems of: brain science, theory and applications of neural networks (both artificial and natural), fuzzy-neural systems, methods and applications of evolutionary algorithms, methods of parallel and mass-parallel computing, problems of soft-computing, methods of artificial intelligence.

Neural Computation《神经计算》（月刊）. Neural Computation disseminates important, multidisciplinary research in theory, modeling, computation, and statistics in neuroscience and in the design and construction of neurally inspired information processing systems. This field attracts psychologists, physicists, computer scientists, neuroscientists, and artificial intelligence investigators working on the neural systems underlying perception, emotion, cognition, and behavior, and artificial neural systems that have similar capabilities. Powerful new experimental technologies being developed by the BRAIN Initiative will produce large, complex data sets, and rigorous statistical analysis and theoretical insight will be essential for understanding what these data mean.

Networks《网络》（一年8期）. Networks publishes material on the analytic modeling of problems using networks, the mathematical analysis of network problems, the design of computationally efficient network algorithms, and innovative case studies of successful network applications.

Network-Computation in Neural Systems《网络：神经系统计算》（季刊）. Network: Computation in Neural Systems is devoted to publishing theoretical neuroscience research that is supported by experimental data with a focus on new technologies.