来源:SCI期刊网 分类:SCI论文发表 时间:2023-11-04 10:36 热度:
人工智能类SCI期刊推荐有哪些呢?SCI属于国际上学术水平较高的期刊,对论文的质量要求是比较高的,投稿之前要查询清楚期刊的内容。SCI分区不同对论文的发表要求也是不同的,接下来,详细的推荐几本期刊,仅供参考。
1、ARTIFICIAL LIFE
学科领域:
大类:计算机科学
小类:计算机:人工智能
中科院分区:4区
期刊简介:Artificial Life, launched in the fall of 1993, has become the unifying forum for the exchange of scientific information on the study of artificial systems that exhibit the behavioral characteristics of natural living systems, through the synthesis or simulation using computational (software), robotic (hardware), and/or physicochemical (wetware) means. Each issue features cutting-edge research on artificial life that advances the state-of-the-art of our knowledge about various aspects of living systems such as:
Artificial chemistry and the origins of life
Self-assembly, growth, and development
Self-replication and self-repair
Systems and synthetic biology
Perception, cognition, and behavior
2、IET Biometrics
学科领域:
大类:计算机科学
小类:计算机:人工智能
中科院分区:3区
期刊简介:The field of biometric recognition - automated recognition of individuals based on their behavioural and biological characteristics - has now reached a level of maturity where viable practical applications are both possible and increasingly available. The biometrics field is characterised especially by its interdisciplinarity since, while focused primarily around a strong technological base, effective system design and implementation often requires a broad range of skills encompassing, for example, human factors, data security and database technologies, psychological and physiological awareness, and so on. Also, the technology focus itself embraces diversity, since the engineering of effective biometric systems requires integration of image analysis, pattern recognition, sensor technology, database engineering, security design and many other strands of understanding.
3、MACHINE LEARNING
学科领域:
大类:计算机科学
小类:计算机:人工智能
中科院分区:3区
期刊简介:Machine Learning is an international forum for research on computational approaches to learning. The journal publishes articles reporting substantive results on a wide range of learning methods applied to a variety of learning problems, including but not limited to:
Learning Problems: Classification, regression, recognition, and prediction; Problem solving and planning; Reasoning and inference; Data mining; Web mining; Scientific discovery; Information retrieval; Natural language processing; Design and diagnosis; Vision and speech perception; Robotics and control; Combinatorial optimization; Game playing; Industrial, financial, and scientific applications of all kinds.
4、Evolving Systems
学科领域:
大类:计算机科学
小类:计算机:人工智能
中科院分区:3区
期刊简介:Evolving Systems covers surveys, methodological, and application-oriented papers in the area of dynamically evolving systems. ‘Evolving systems’ are inspired by the idea of system model evolution in a dynamically changing and evolving environment. In contrast to the standard approach in machine learning, mathematical modelling and related disciplines where the model structure is assumed and fixed a priori and the problem is focused on parametric optimisation, evolving systems allow the model structure to gradually change/evolve. The aim of such continuous or life-long learning and domain adaptation is self-organization. It can adapt to new data patterns, is more suitable for streaming data, transfer learning and can recognise and learn from unknown and unpredictable data patterns. Such properties are critically important for autonomous, robotic systems that continue to learn and adapt after they are being designed (at run time).
文章名称:人工智能类SCI期刊推荐