Información de la Revista
Information Fusion
http://www.journals.elsevier.com/information-fusion
Factor de Impacto:
12.97
Editor:
Elsevier
ISSN:
1566-2535
Vistas:
18745
Seguidores:
25
Solicitud de Artículos
The journal is intended to present within a single forum all of the developments in the field of multi-sensor, multi-source information fusion and thereby promote the synergism among the many disciplines that are contributing to its growth. The journal is the premier vehicle for disseminating information on all aspects of research and development in the field of information fusion. Articles are expected to emphasize one or more of the three facets: architectures, algorithms, and applications. Papers dealing with fundamental theoretical analyses as well as those demonstrating their application to real-world problems will be welcome. The journal publishes original papers, letters to the Editors and from time to time invited review articles, in all areas related to the information fusion arena including, but not limited to, the following suggested topics:

• Data/Image, Feature, Decision, and Multilevel Fusion
• Multi-classifier/Decision Systems
• Multi-Look Temporal Fusion
• Multi-Sensor, Multi-Source Fusion System Architectures
• Distributed and Wireless Sensor Networks
• Higher Level Fusion Topics Including Situation Awareness And Management
• Multi-Sensor Management and Real-Time Applications
• Adaptive And Self-Improving Fusion System Architectures
• Active, Passive, And Mixed Sensor Suites
• Multi-Sensor And Distributed Sensor System Design
• Fusion Learning In Imperfect, Imprecise And Incomplete Environments
• Intelligent Techniques For Fusion Processing
• Fusion System Design And Algorithmic Issues
• Fusion System Computational Resources and Demands Optimization
• Special Purpose Hardware Dedicated To Fusion Applications
• Mining Remotely Sensed Multi-Spectral/Hyper-Spectral Image Data Bases
• Information Fusion Applications in Intrusion Detection, Network Security, Information Security and Assurance arena
• Applications such as Robotics, Space, Bio-medical, Transportation, Economics, and Financial Information Systems
• Real-World Issues such as Computational Demands, Real-Time Constraints in the context of Fusion systems.
Última Actualización Por Dou Sun en 2022-01-29
Special Issues
Special Issue on Multi-source data fusion for sustainable cities
Día de Entrega: 2024-06-03

With the rapid growth of urban areas and the increasing challenges posed by climate change and resource scarcity, the concept of sustainable cities has gained significant attention. Sustainable cities are those that prioritize the efficient use of resources, minimize environmental impact, and enhance the quality of life for their residents. To effectively address these challenges and achieve sustainable urban development, it is essential to harness the power of multi-source data fusion techniques. By integrating data from various sources such as sensors, satellites, social media, and citizen-generated data, we can gain valuable insights into urban systems and implement effective strategies for sustainable urban planning and management. Multi-source data fusion plays a crucial role in sustainable cities by providing a comprehensive and holistic understanding of urban environments. However, existing approaches often fall short in building sustainable cities due to their limitations in their scope and coverage. Furthermore, different data sources often have varying formats, resolutions, and quality, making it challenging to combine them effectively. Lastly, sustainable urban development requires a multidisciplinary approach, considering social, economic, and environmental factors. To overcome these limitations and advance sustainable urban development, multi-source data fusion techniques provide a promising solution. The proposed special issue aims to explore the latest advancements, methodologies, and case studies in multi-source data fusion for sustainable cities, facilitating the development of innovative solutions and practical applications to address the pressing challenges. We welcome the submission of original research articles, case studies, and review articles that provide unique perspectives, empirical evidence, or theoretical advancements in the field of data fusion techniques for sustainable cities. All submissions to this special issue will undergo a thorough peer-review process to ensure the publication of exceptional and influential work. The main objective of this issue is to emphasize the practical application of data fusion techniques, aiming to foster the creation of intelligent and sustainable cities that benefit both society and the environment. Topics include (but are not restricted to): Multi-modal data fusion for sustainable transportation planning and management. Integration of data from heterogeneous sources, such as GPS, cameras, and crowdsourced data. Data quality assessment and data preprocessing techniques in multi-source data fusion. Applications of multi-source data fusion in traffic flow modeling, prediction, and control. Fusion of socio-economic data for understanding social sustainability. Data fusion for optimizing energy generation, delivery, consumption and demand in cities. Multi-source data fusion for autonomous vehicles, transportation network optimization and routing. Privacy and security issues in the fusion of sensitive urban data. Integration of spatial and temporal data for urban sustainability analysis. Guest editors: Dr. P.N. Suganthan, PhDKINDI Center for Computing Research, Qatar University, Doha, Qatar(randomization-based learning methods, swarm, andevolutionary algorithms, pattern recognition, deep learning and applications of the swarm, evolutionary & machine learning algorithms) Dr. Ruobin Gao, PhDSchool of Civil and Environmental Engineering, Nanyang Technological University, Singapore(machine learning, randomized neural networks, time series forecasting, and artificial intelligence for the maritime industry.) Dr. Ryan Wen Liu, PhDHubei Key Laboratory of Inland Shipping Technology, School of Navigation, Wuhan University of Technology, Wuhan, China(intelligent transportation system, intelligent vehicle, multi-sensor data fusion, computer vision, trajectory data mining) Manuscript submission information: The journal's submission platform (Editorial Manager®) will be available for receiving submissions to this Special Issue from October 9th, 2023. Please refer to the Guide for Authors to prepare your manuscript and select the article type of “VSI: MDF for SC” when submitting your manuscript online. Both the Guide for Authors and the submission portal could be found on the Journal Homepage: Information Fusion | Journal | ScienceDirect.com by Elsevier. Timeline: Submission Open Date *09/10/2023 Final Manuscript Submission Deadline *03/06/2024 Editorial Acceptance Deadline *01/07/2024
Última Actualización Por Dou Sun en 2023-11-11
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