The Official Journal of the World Federation on Soft Computing (WFSC) http://www.softcomputing.org

Applied Soft Computing is an international journal promoting an integrated view of soft computing to solve real life problems. Soft computing is a collection of methodologies, which aim to exploit tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost. The focus is to publish the highest quality research in application, advance and convergence of the areas of Fuzzy Logic, Neural Networks, Evolutionary Computing, Swarm Intelligence and other similar techniques to address real world complexities.

Applied Soft Computing is a rolling publication: articles are published as soon as the editor-in-chief has accepted them. Therefore, the web site will continuously be updated with new articles and the publication time will be short.

Major Topics:

The scope of this journal covers the following soft computing and related techniques, interactions between several soft computing techniques, and their industrial applications:

    Evolutionary Computing
    Fuzzy Computing
    Hybrid Methods
    Immunological Computing
    Neuro Computing
    Swarm Intelligence
    Machine and Deep Learning
    Rough Sets

The application areas of interest include but are not limited to applications of soft computing to:

    Agricultural Machinery, Smart Farming
    Autonomous Reasoning
    Big Data, IoT, Edge Computing
    Combinatorial Optimization
    Data Mining
    Decision Support
    Engineering Design Optimization
    Fault Diagnosis
    Finance
    Human-Machine Interface
    Intelligent Agents
    Manufacturing Systems
    Power Electronics
    Multi-objective Optimization
    Power and Energy
    Process and System Control
    Robotics
    Security
    Sensor Systems
    Signal or Image Processing
    Software Engineering
    Supply Chain Economy
    System Identification and Modelling
    Telecommunications
    Time Series Prediction
    Extended Reality, Metaverse, Digital Twins
    Vision or Pattern Recognition

Authors are welcome to submit letters promoting original soft computing research to Applied Soft Computing's open access companion title, Systems and Soft Computing.

Special Issue on Quantum Computational Intelligence for Real-World Issues and Challenges
提出日: 2024-12-15

The term “Computational intelligence” (CI) refers to a set of nature-inspired computational approaches for solving complex real-world problems that are otherwise difficult to solve by the mathematical or traditional modeling owing to the complexity and underlying uncertainties in the process manifestations or the scholastic nature of the processes. CI combines five main complementary techniques: fuzzy logic, artificial neural networks, evolutionary computing, learning theory, and probabilistic methods. Apart from these, several biologically inspired swarmintelligent algorithms also enrich the CI domain.

Special issue information:

1. Siddhartha Bhattacharyya (Corresponding Guest Editor), VSB Technical University of Ostrava, Czech Republic. E-mail: dr.siddhartha.bhattacharyya@gmail.com
2. Mario Koeppen, Fukuoka Institute of Technology, Japan. 
3. Ivan Zelinka, VSB Technical University of Ostrava, Czech Republic. 
4. Ugo Fiore, University of Salerno, Italy. 
5. Hendrik Richter, HTWK Leipzig University of Applied Sciences, Germany. 

Manuscript submission information:

Of late, scientists have focused on a new computing paradigm inspired by the principles of quantum mechanics. This new computing paradigm, Quantum Computing, promises to be a viable alternative for solving complex problems that classical computers would either be unable to solve or take several years to complete. Quantum computing is fundamentally a synergistic combination of fields from quantum physics, classical information theory, and computer science. The quantum computing alternative yields more time-efficient and robust solutions to highly complex problems over traditional computing. They possess faster data processing capabilities (even exponentially)

As such, researchers have coupled the underlying principles of quantum computing into the CI framework to introduce different quantum CI algorithmic approaches. Real-world quantum computing platforms have also become available recently and allow the use of new algorithms "in vivo”. The advantages of these quantum algorithms have become prominent in yielding real-time outputs and faster convergence speed.

The main objective of this Special Issue is to bring together recent advances and trends in methodological approaches, theoretical studies, and mathematical and applied techniques related to addressing real-world issues and challenges using quantum computational intelligence.

We invite researchers to contribute original work related to the theoretical advancements in this field with applications to different real-world problems. We are soliciting contributions on (but not limited to) the following:

 Quantum Computational Intelligence
 Quantum Neural Networks
 Quantum Reinforcement Learning
 Quantum Clustering
 Quantum AI Generative Models
 Quantum Evolutionary Algorithms
 Quantum Inference, Reasoning, and Decision-Making
 Quantum Robotics and Control Systems
 Quantum Natural Language Processing
 Quantum Image and Signal Processing
 Software and Compilers for Quantum CI
 Quantum Error Correction and Mitigation
 Quantum Gate Synthesis
 Quantum Algorithms and Circuits Design Optimization
 Quantum Internet and Quantum Communication
 Quantum Sensors, Quantum Sensing, and Measurement Systems
 Multilevel Quantum Systems
 Neutrosophic Quantum Systems

This SI will follow the peer-review process of the Applied Soft Computing, Elsevier
(https://www.sciencedirect.com/journal/applied-soft-computing/publish/guide-for-authors) and
operates on a single anonymized review process.

After an initial assessment of the suitability and scope of the submissions by the guest editors, the
submissions will be evaluated based on their originality, presentation, relevance, contributions, and suitability to the special issue. Submissions that do not match 100% with the goals and scope of this journal, as well as submissions lacking novelty, significance, apparent contribution, or do not fit within the scope of the special issue, will be summarily rejected.

During submission through the journal editorial manager, the authors have to select an Article
Type. "VSI: QuantumML".

Important dates:

● Submission Opens: June 2024
● Submission Deadline: October 2024
● Tentative Publication: May 2025

Special Issue on Sustainable Cities: Using Large Language Models to Promote Innovation and Development
提出日: 2025-03-11

This Special issue aims to explore and promote innovation in sustainable cities by applying Large Language Models (LLMs), such as GPT-3 and its successors. LLMs harness cutting-edge technology, such as natural language processing and artificial intelligence, with immense potential for addressing complex issues, including optimized land use and designing green space to develop sustainable infrastructure, better traffic planning to save fuel and time of the citizens, and predicting future needs for producing the exact requirements. Moreover, LLMs can optimize energy consumption within cities by helping manage energy grids, monitor energy usage, andsuggest ways to reduce it, a paramount concern for achieving sustainability and reducing cities' carbon footprint. Additionally, LLMs can monitor air quality, water quality, and pollution levels, providing real-time data that can help cities promptly address environmental issues for better resource management and a healthier urban environment. More importantly, LLMs can support the creation of inclusive policies for identifying underserved communities, recommend social programs, and assist policymakers in promoting social equity within cities.

Guest editors:

1. Chien-Ming Chen, Nanjing University of Information Science and Technology, China,
chienmingchen@ieee.org

2. Bing Xue, IEEE Fellow, Victoria University of Wellington, New Zealand (Female Academician),
bing.xue@vuw.ac.nz

3. Jerry Chun-Wei Lin, IET Fellow, Western Norway University of Applied Sciences, Norway,
jerrylin@ieee.org

4. Muhammad Naveed Aman, University of Nebraska-Lincoln, USA,
naveed.aman@unl.edu

5. Mu-En Wu, National Taipei University of Technology, Taiwan,
mnwu@ntut.edu.tw

Manuscript submission information:

This Special Issue will provide insights into how researchers, policymakers, andpractitioners can harness LLMs to drive innovation and development in sustainable cities. Through papers and case studies, we will showcase the practical impact of LLMs in addressing urban challenges and achieving sustainable goals.

The Special Issue will explore, but is not limited to, the following themes:

    Sustainable Urban Planning and Design by LLM;
    LLM-enabled Urban Transportation and Intelligent Transport;
    Sustainable Energy Management by LLM;
    LLM-based Urban Environmental Conservation;
    LLM-Driven Social Inclusivity and Public Policies;
    Sustainable Urban Data Analytics by LLM
    LLM-enabled Waste Management
    Crisis Response and Optimization by LLM
    Urban Green Initiatives by LLM
    LLM-driven Public Health programs
    Disaster Preparedness with LLM.
    Analyzing Production and Consumption insights for mitigating ecology disturbance
    LLM for building sustainable Architecture and Infrastructure
    Community Engagement through LLM

Important date:

Deadline for Submission: 30 Dec. 2024
Final Decision:01 March. 2025

Special Issue on Intelligent Decision Making, Deep and Machine Learning, Generative AI to Empower Smart Production and Service
提出日: 2025-05-31

Deep and machine learning, swarm intelligence, big data analytics, generative artificial intelligence, and LLM (Large Language Model) are increasingly developed for intelligent decision making involved in smart production and service in various industrial contexts. To meet with various needs of different customers, paradigm is shifting from mass production and mass-customization towards personalization and flexibility for smart production and service. In addition to the challenges in real settings, more opportunities are made available by state-of-the-art soft computing and AI technologies to empower novel applications for smart production and service to enhance supply chain resilience and change the business ecosystem.

Guest editors:

Dr. Chen-Fu Chien, National Tsing Hua University, Taiwan;
Dr. Kanchana Sethanan, Department of Industrial Engineering, Khon Kaen University, Thailand;
Dr. Run-Liang Dou, Department of Information Management and Management Science, Tianjin University, China;
Dr. Rapeepan Pitakaso, Department of Industrial Engineering, Ubon Ratchathani University, Thailand;
Dr. Chia-Yu Hsu, Department of Industrial Management, National Taiwan University of Science and Technology, Taiwan

Manuscript submission information:

Flexible decisions and intelligent decision making involved in production and service processes, manufacturing networks, supply chain management, and industry ecosystem are critical to enhance the efficiency and effectiveness of human-system collaborations to empower smart production and service.

This special issue of the Applied Soft Computing aims to address research issues involved in shifting paradigms driven by the developments of intelligent decision making, deep and machine learning, swarm intelligence, big data analytics, generative artificial intelligence, and LLM for smart production and service in various industrial contexts. Empirical studies with technical and/or methodological advances to address realistic issues are encouraged. In particular, high-tech industries such as semiconductor industries consist of complex and lengthy manufacturing processes with tightly constrained processing technologies, reentrant process flows, sophisticated equipment, volatile demands, and high product mix. While big data is accumulated via the fully automated production and service facilities and supply chain management systems, various solutions and techniques can be developed to empower intelligent decision making to address new challenges in real time.

Scope of this Virtual Special Issue:

Topics to be covered include the application of the following artificial intelligence and soft computing methodologies and interactions between several soft computing techniques:

    Ant Colony Optimization  
    Artificial Intelligence  
    Big Data Analytics  
    Convolutional Neural Networks 
    Deep and Machine Learning  
    Evolutionary Computing  
    Fuzzy Computing  
    Generative AI  
    Hybrid Methods  
    Immunological Computing  
    Intelligent Decision-Making Technologies  
    LLM (Large Language Model)  
    Neuro Computing  
    Particle Swarm Optimization  
    Probabilistic Computing  
    Rough Sets  
    Wavelet 

to address critical, not restricted to the following aspects of smart production in real settings:

    Advanced equipment/process control (AEC/APC)  
    Automated material handling systems (AMHS), automatic guided vehicle (AGV)
    Intelligent Decision technologies for Real-time Decision
    Equipment diagnosis, Predictive maintenance, and Tool Health
    Factory modeling, analysis and performance evaluation
    Flexible Production Planning & Scheduling
    Industry 4.0 & Manufacturing Strategy
    Intelligent systems & Robots
    Manufacturing Intelligence & Manufacturing Informatics
    Mass personalization and customization
    Predictive Maintenance
    Smart Decision for Corporate Resource Planning & Allocation
    Sustainability and circular economy
    Virtual Reality (VR), Augmented Reality (AR), Mixed Reality (MR)
    Yield enhancement and e-Diagnosis

Important date:

Deadline for Submission: 31 May, 2025
Final Decision: 31 August, 2025