Impact Score 2.15
A Special Issue in Memetic ComputingOpen to submissions until October 1 2021
A smart city refers to the effective integration of physical, digital, and human systems to deliver a sustainable, prosperous, and inclusive future for citizens. Due to the increasing number of citizens, buildings, vehicles, and other public/personal service providers, smart city management with respects to efficiency, safety, sustainability, and humanity involves many urgent and challenging tasks, as hierarchical and heterogeneous stakeholders are interconnected and correlated, such as, communities, energy & water networks, and transportation systems. Recent development of smart sensors, and other Internet of Things (IoTs), make large amounts of city-level data available, which brings great opportunities for smart city management. Intensive studies have started to develop simulation, visualization, and other big data processing methods for modeling urban systems, citizen behavior, and social dynamics, but the efficiency of data processing is deteriorated exponentially as the increase of data volume. New computing technologies, such as, memetic computing, distributed optimization, and transfer learning, are borrowed and implemented for exploiting similarities of multiple computing tasks and providing smart city services cooperatively. As a result, data-centric memetic computing technologies have become hot topics in intelligent transportation systems, smart energy systems, smart government platforms, urban safety, smart medicines, and so forth.
Due to big data of smart city, many computing technologies often show inefficiency or even incapability with respect to data storage, communication, feature selection, data mining, and decision making. To cope with big data arisen in smart cities, a straightforward way is to exploit similarity of data characteristics, and domain knowledge. It can be expected that the solution of a specific task can benefit its similar tasks by sharing data model or knowledge, and the learning speed and modelling accuracy could be significantly improved. Socio-cultural notion of memes into artificial systems, could be a useful tool to enhance the efficacy of computational techniques through explicit prior knowledge incorporation and transfer learning. Memetic computation is a paradigm that uses the memes as units of information encoded in computational representations (e.g., local search heuristics, fuzzy rules, neural models, etc.), covering a plethora of potential meme-inspired computing methodologies, frameworks, and operational algorithms. With prior knowledge of urban systems, memetic computing plays effective roles as a form of individual learning procedure or local search operator to enhance the performance of planning and scheduling optimization algorithms. In other smart city applications, data has similar characteristics, and domain knowledge in one city can be incorporated into other similar cities. Memes as the building blocks of specific domain, can perhaps be effectively transferred into data-centric tasks of other similar cities.
The goal of this Special Issue is to collect new ideas and contributive applications of memetic computing in a smart city, including intelligent transportation, smart grid, sensor networking, etc. The Special Issue invites industry and academic researchers in computer science and engineering, electrical engineering, and civil engineering, as well as other multi-disciplinary engineers and professionals, to contribute original articles on all aspects of data-centric smart city and memetic computing technologies.
Topics of interest include, but are not limited to:
Key DatesSubmission deadline: October 1, 2021First-round review result: November 30, 2021Revision deadline: December 31, 2021Second-round review result: February 15, 2022Final acceptance: March 1, 2022
Guest EditorsZhou Wu, Chongqing University, ChinaMin Jiang, Xiamen University, ChinaLiang Feng, Chongqing University, ChinaLijun Zhang, Huazhong University of Science and Technology, China