2022 7th International Conference on Computational Intelligence and Applications (ICCIA 2022)

2022 7th International Conference on Computational Intelligence and Applications  (ICCIA 2022), will be held in Nanjing, China, during June 24-26, 2022, sponsored by Nanjing Tech University, China, co-sponsored by College of Electrical Engineering and Control Science, Nanjing Tech University, China.

2021 6th International Conference on Computational Intelligence and Applications (ICCIA 2021) is the premier forum for the presentation of new advances and research results in the fields of theoretical, experimental, and applied Computational Intelligence and Applications.The conference will bring together leading researchers, engineers and scientists in the domain of interest from around the world.

The CFP brochure can be downloaded here.

Topics of interest for submission include, but are not limited to:

Fuzzy Theory and System/模糊理论与系统

Fuzzy Systems

· 模糊系统

Fuzzy logic and fuzzy set theory

· 模糊逻辑与模糊集合论

Fuzzy-neuro-evolutionary -rough hybrids

· 模糊神经进化粗糙杂种

Fuzzy and rough data analysis

· 模糊粗略的数据分析

Fuzzy optimization and design

· 模糊优化与设计

Fuzzy decision making

· 模糊决策

Fuzzy systems modeling and identification

· 模糊系统建模与识别

Fuzzy mathematics

· 模糊数学

Fuzzy systems architectures and hardware

· 模糊系统架构和硬件

Fuzzy pattern recognition

· 模糊模式识别

Fuzzy image processing

· 模糊图像处理

Fuzzy control and systems

· 模糊控制和系统

Fuzzy data mining and forecasting

· 模糊数据挖掘与预测

Fuzzy information processing

· 模糊信息处理

Fuzzy human interface

· 模糊的人机界面

Fuzzy internet and multimedia

· 模糊的互联网和多媒体

Fuzzy computing with words

· 用词进行模糊计算

Pattern recognition

· 模式识别

expert system

· 专家系统

Artificial Neural Networks/人工神经网络

Artificial immune systems

· 人工免疫系统

Artificial life

· 人工生命

Associative memories

· 联想记忆

Brain Imaging and neural information processing

· 脑成像和神经信息处理

Brain compuComputational neuroscienceter interface

· 脑计算计算神经科学接口

Connectionist theory and cognitive science

· 联结主义理论和认知科学

Classifier systems

· 分级系统

Cognitive systems and applications

· 认知系统和应用

Mathematical modeling of neural systems

· 神经系统的数学建模

Neuroinformatics and bioinformatics

· 神经信息学和生物信息学

Neural Networks

· 神经网络

Neurodynamic analysis

· 神经动力学分析

Neurodynamic optimization and adaptive dynamic programming

· 神经动力学优化和自适应动态规划

Learning rules and methods

· 学习规则与方法

Supervised, unsupervised and reinforcement learning

· 有监督、无监督和强化学习

Intrusion detection and fault diagnosis

· 入侵检测与故障诊断

Embedded neural systems

· 嵌入式神经系统

Estimation of Distribution Algorithms

· 分布算法的估计

Time series analysis

· 时间序列分析

Evolutionary Computing/进化计算

Ant colony optimization

· 蚁群优化

Coevolution and collective behaviour

· 共同进化和集体行为

Combinatorial and numerical optimization

· 组合和数值优化

Constraint and uncertainty handling

· 约束和不确定性处理

Differential evolution Data mining

· 差分进化数据挖掘

Evolutionary computation for bioinformatics

· 生物信息学的进化计算

Evolutionary computation in dynamic and uncertain environments

· 动态和不确定环境中的进化计算

Evolutionary computer vision

· 进化计算机视觉

Evolutionary data mining

· 进化数据挖掘

Evolutionary design

· 进化设计

Evolutionary games

· 进化游戏

Evolutionary intelligent agents

· 进化智能代理

Evolutionary learning systems

· 进化学习系统

Evolutionary robotics

· 进化机器人

Evolutionary techniques in economics, finance and marketing

· 经济、金融和市场营销中的进化技术

Evolvable hardware and software

· 可进化的硬件和软件

Evolving neural networks and fuzzy systems

· 进化的神经网络和模糊系统

Granular computing

· 粒计算

Hybrid optimisation algorithms

· 混合优化算法

Hybrid intelligent systems

· 混合智能系统

Robotic and control applications

· 机器人和控制应用

Swarm Intelligence

· 群体智能

Theory of evolutionary computation

· 进化计算理论

Molecular and quantum computing

· 分子和量子计算

Computational Intelligence (CI), as an offshoot of the subject of Artificial Intelligence (AI), is a research field of studying various tools such as fuzzy logic, neuro networks, genetic algorithms, etc. Growing technical achievements to gather and integrate multi-“style” data from sensors, mobile devices, social media, log files, cameras, microphones etc. provide useful information about the state and the environment of the data sources, but also result in large and complex data sets, known as Big Data, which requires more efficient and powerful data analysis methods and applications.

Recently, the great breakthroughs, Convolutional Nets in Deep Learning, in the field of Computational Intelligence have tremendously attracted the sights of researchers and aroused their enthusiasms in exploring broader applications of the CI solutions to “Big Data” problems. Deep Learning, as a core domain of CI, provides more efficient algorithms to deal with large-scale data in neuroscience, computer vision, speech recognition, language processing, biomedical informatics, recommender systems, learning theory, robotics, gaming theory. DL is gaining applications in many domains due to the availability of large amount of data coupled with machine learning algorithms.  As an increasing trend, it is necessary to establish a research forum that will enable to identify the emerging trends in the domain. As a huge part of “Big Data” comes from social networks, understanding and representations of texts in Natural Languages (NL) play an extremely important role and it is indispensable to bring Computational Semantics elements into CI to provide a true machine understandable, interactive, and communicable environment. To meet these requirements, ICCIA will provide researchers and practitioners an effective forum to exchange their latest findings and achievements in the fields of Computational Intelligence.