Calls for Papers (special): International Journal of Swarm Intelligence Research (IJSIR)


Special Issue On: Swarm Intelligence in Data Mining

Submission Due Date
5/30/2018

Guest Editors
Sujata Dash, North Orissa University, India
Atta-ur-Rahman, CCSIT, Imam Abdulrahman Bin Faisal University, Saudi Arabia
Sliman Layth, Efrei Paris, 30 Avenue de La République, France

Introduction
Data mining is one of the most researched areas in current era of technology due to its tremendous applications in almost every field of study regardless of the domain and discipline. For example, business intelligence, big data, information extraction, information retrieval, trend analysis, prediction, forecasting, approximation etc. are few of many applications of data mining. Moreover, its importance is increasing with almost same proportion as data volumes across the globe are increasing. Because there is more data, more sophisticated data mining is required. Hence it is a never ending endeavor. A variety of techniques have been augmented with the data mining for sake of enhancing optimization and further improvement in terms of accuracy and precision. These techniques are statistical, stochastic, evolutionary etc. Swarm intelligence is one of the most successful candidates among such techniques that has been evolving rigorously over past decades and working as a catalyst to plenty of existing techniques. Its intersection with data mining has been producing wonderful outcomes by boosting up various factors like convergence, accuracy and precision. In swarm intelligence the algorithms are motivated and inspired by the nature and natural phenomena exist in various species like ants, bees, spiders etc. In this regard various techniques have been introduced like Particle Swarm Intelligence (PSO), Ant Colony Optimization (ACO) and Artificial Bee Colony Optimization (ABC) are few of such techniques.

Objective
This special issue aims to capture some of these efforts so that they can contribute towards further analysis and progress. Papers are invited which look at the issues of applications of swarm intelligence in data mining.

The objective of this special issue is to bring together researchers from (i) various areas where data mining problems arise regardless of the domain and (ii) from the field of swarm intelligence individually and their hybridization. It is also expected that significant methodological progress in swarm intelligence can be stimulated because most of the applications today focus on smaller types of problems, so the suitability and effectiveness of the methods for larger problems is not obvious.

Short listed and accepted papers will be published in IGI Goble, International Journal of Swarm Intelligence Research (IJSIR) which is indexed by ISI web of science (WoS).

Recommended Topics
Topics to be discussed in this special issue include (but are not limited to) the following:

• Applications of Swarm Intelligence in Decision support systems
• Applications of Swarm Intelligence in Information extraction and retrieval
• Applications of Swarm Intelligence in Knowledge and data discovery
• Applications of swarm intelligence in Block chain
• Applications of swarm intelligence in IoT
• Applications of swarm intelligence in social media
• Swarm intelligence and optimization
• Cuckoo search
• Bee algorithms
• Firefly algorithms
• Data, Text, image, video analysis and mining
• Routing and scheduling optimization
• Ant colony optimization
• Genetic algorithms
• Big data analytics
• Intelligent information technology
• Intelligent agents and nature-inspired computing
• Large-scale logistics and production planning
• Computational biology
• Web mining


Submission Procedure
Researchers and practitioners are invited to submit papers for this special issue on “Swarm Intelligence in Data Mining on or before May 30, 2018. All submissions must be original and may not be under review by another venue. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All submissions and inquiries should be directed to the attention of:
Sujata Dash, Atta-ur-Rahman & Sliman Layth
Guest Editors
International Journal of Swarm Intelligence Research (IJSIR)
E-mail: sujata238dash@gmail.com, aaurrahman@iau.edu.sa, layth.sliman@gmail.com

Special Issue On: Bio Inspired and Soft Computing Methods for Solving Time Series Problems

Submission Due Date
6/30/2018

Guest Editors
Dr. Habib Shah, College of Computer Science, King Khalid University, Abha, Kingdom of Saudi Arabia

Introduction
Bio-inspired and soft computing methods have motivated scientific researchers to enhance the nature attractive behaviours of birds, fishes, animals, insects for solving complex nonlinear science, engineering, economical, medical and metrological problems. These methods are comparatively efficient than typical algorithms. How to use bio-inspired and efficient soft computing and computational methods for solving time series problems especially with complex, noisy and natural dataset to provide economic stability and security of human being like: Univariate and Multivariate Financial, Stock Exchange, Crude Oil Time Series, Natural Disasters Earthquake, Floods, Tsunami, Ozone Gas, Wildfire, Volcanoes, Heat Waves Temperature, weather, Storm Time Series and Medical time series dataset like breast cancer, Breast Tissue, Diabetes, X-Ray and others different types for time series dataset. The latest and hybrid bio-inspired methods will be used for prediction/ forecasting, detection and classification tasks through different computational tools. The success of bio-inspired and soft computing methods depends on the variety of algorithms and techniques that usually belong to one of the main learning styles: supervised, unsupervised, and reinforcement learning.

Objective
This special issue aims to demonstrate how soft computing and bio inspired learning algorithms have contributed, and are contributing to the research and applications of prediction, detection and classification of complex and nature time series dataset. This issue seeks to publish unique research and reflect the most recent advances and the latest contributions of optimization in the subject areas below, covering soft computing and recent bio inspired based learning algorithms. The field of bio inspired and soft computing methods are vast, flexible, and interesting, therefore, the scope of this special issue has been kept wide and following are the topics covered in this special issue

Recommended Topics
Topics to be discussed in this special issue include (but are not limited to) the following:

  • African Buffalo Search
  • Artificial Bee Colony
  • Ant Colony
  • Particle Swarm Optimization
  • Hybrid bio inspired methods
  • Cuckoo Search
  • Evolutionary algorithms
  • Fish Schooling
  • Bee Colony optimization
  • Artificial immune systems
  • Case based reasoning
  • Computational Statistics
  • Genetic algorithms
  • Hybrid intelligent systems
  • Intelligent systems
  • Nature inspired computing


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Bio Inspired & Soft Computing Methods for solving Time Series problems on or before June 30, 2018. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All submissions and inquiries should be directed to the attention of:
Dr. Habib Shah
Guest Editor
International Journal of Swarm Intelligence Research (IJSIR)
E-mail: habibshah.uthm@gmail.com

Special Issue On: Swarm Intelligence in Ecological System Modelling

Submission Due Date
8/31/2018

Guest Editors
Mohamed Elhadi Rahmani, GeCoDe Laboratory, University of Saida, Algeria
Abdelmalek Amine, GeCoDe Laboratory, University of Saida, Algeria

Introduction
Computer modeling of ecological systems is the activity of implementing computer solutions to analyze data related to the fields of remote sensing, earth science, biology and oceans. The ecologists analyze the data to identify the relationships between a response and a set of predictors, using statistical models that do not accurately describe the main sources of variation in the response variable. Knowledge discovery techniques are often more powerful, flexible and effective for exploratory analysis than statistical techniques. Data mining is not only a matter of grouping or classifying data but optimizing exploration itself is an area of major importance in engineering fields in general. The problems NP-Hard Are difficult problems to be solved by conventional techniques. The increase of such kinds of problems has created an active research topic, from which researchers try to develop mathematical techniques to find the best possible solutions for a given problem. Optimization methods are divided into two categories: deterministic methods that are the oldest. These methods require a great effort to make calculations, which gives a greater limit in terms of complexity when the size of the problem increases. This gives the motivation to invent new techniques which consist in using a random computation and a local search to solve an optimization problem based on iterative improvements of a population of solutions or a unique solution. These methods have been brought together in a field called Bio-inspiration and meta-heuristics. One of the most successful techniques in bio-inspiration and meta heuritsics, are swarm intelligence. A swarm-based algorithm is an algorithm from which the solutions present particles with irregular movements in the search space. These algorithms are decentralized and self-organized processes in food research.

Objective
This special issue aims to collect new original researches that apply swarm intelligence techniques on ecological system data modelling. New contributions are welcomed as well as state of the art of application of swarm intelligence to analyze ecological data.

Recommended Topics
Topics to be discussed in this special issue include (but are not limited to) the following:

• Agricultural data analysis.
• Climatology.
• Food Safety.
• Environmental issues in rural and urban areas.
• Soil air and water quality analysis.
• Geographic Information Systems.
• Environmental change and human development.
• Environmental informatics.
• Renewable energy sources and uses.
• Remotely sensed data collection, analysis, interpretation and display.
• Surveying from space, air, water and ground platforms.
• Forestry.
• Aquatic systems.
• Seismic hazards detection.


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Swarm Intelligence in ecological system modelling on or before August 31, 2018. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS athttp://www.igi-global.com/publish/contributor-resources/before-you-write//. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All submissions and inquiries should be directed to the attention of:
Mohamed Elhadi Rahmani
Guest Editor
International Journal of Swarm Intelligence Research (IJSIR)
E-mail: r_m_elhadi@yahoo.fr

Special Issue On: Swarm Intelligence Techniques for Social Media Systems

Submission Due Date
9/1/2018

Guest Editors
Dr. Anuja Arora, Jaypee Institute of Information Technology, Noida, India
Dr. Divakar Yadav, Madan Mohan Malviya University of Technology, Gorakhpur, India,
Dr. Susan Swayze, Associate Professor, Educational Research, Graduate School of Education and Human Development

Introduction
The Special Issue titled “Swarm Intelligence Techniques for Social Media Systems” invites quality, original and unpublished research articles. In this modern age, huge amounts of content is posted daily by end users through various social media platforms, like Facebook, Twitter, Pinterest, Blogging sites, Forum Sites, and social coding community, on all possible domains such as Ecommerce, News, Marketing, Recruitment, Software Development, Politics, etc. An emerging area of research embraces the notions that social media, stock market, and marketing are basically complex studies and their behavior is difficult to predict.

Objective
This special issue is a premier venue to deal with the swarm intelligent aspect of social computing. Swarm Intelligence encompasses ant colony optimization, particle swarm oprimization, social agents, flocking behavior, evolutionary agents- Genetic Algorithm, and multi-objective optimization. Recent years have seen tremendous studies on leveraging social media analysis using swarm intelligent techniques and have shown promising results to solve various domain issues. In this digital era, data is being generated at an exponential rate through varied social media applications. The emerging and developing social data offers different challenges and can be resolved by deploying swarm techniques. They need to be customized, adapted and subsequently disseminated. Swarm Intelligence methodologies are successfully helping in big data and thus are open to a plethora of large scale social media applications. Social Media systems are driving contemporary issues and require swarm approaches to resolve.

As a result, there is a need for further research to explore swarm intelligent paradigm to utilize social media data to capture various insights from enormous amount of user generated content on social media platforms and sustain competitive advantages.

Recommended Topics
Topics to be discussed in this special issue include (but are not limited to) the following:

• Swarm intelligence in digital marketing
• Swarming behavior of social insects
• Web Social Swarming
• Social pattern detection
• Swarm techniques for marketing, ecommerce applications
• Web Social Swarming
• Opinion mining
• Agent based social system modeling
• Social Agents
• Agents queuing and homing
• Particle Swarm Optimization for Social Media and Social Network.
• Ant Colony marketing
• ACO in online social media and social network
• Community detection in social network using swarm algorithms
• Clustering social network using swarm optimization algorithms
• Ant’s Social network
• Social market movement prediction
• Machine Learning algorithms on Social Network/ Media applications
• Social Big Data
• Artificial Intelligence for revolutionize Social Media
• Social Listening
• Swarm techniques for Social Recommendation.
• Social Cloud and analytics using Swarm Intelligence
• Optimization in social media environment
• Statistical Learning of Social Media
• Social evolutionary agents- genetic algorithm
• Social network multi objective optimization using GA
• Real-World Applications
• Social media security using swarm intelligence


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Swarm Intelligence Techniques for Social Media Systems on or before 1st September 2018. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All submissions and inquiries should be directed to the attention of:
Dr. Anuja Arora
Guest Editor
International Journal of Swarm Intelligence Research (IJSIR)
E-mail: anuja.arora29@gmail.com

Special Issue On: Bio-inspired Optimization Algorithms and their Applications

Submission Due Date
10/24/2018

Guest Editors
Dr. Pandian Vasant, Universiti Teknologi PETRONAS, Malaysia
Prof. Igor Litvinchev,Nuevo Leon State University (UANL), Mexico
Dr. Van Van Huynh, Ton Duc Thang University, Vietnam

Introduction
Bio-inspired optimization algorithms and optimization approaches are becoming very famous in the research area of artificial intelligence. Many real world and large scale problems, as well as many-objectives problems, can be successfully solved by bio-inspired optimization techniques. This biologically natured novel technique has been a cutting edge research methodology to most of researchers across the planet.

Objective
The main goal of this special issue is to bring in the hidden innovation and creative methodologies and its application in Bio-inspired Optimization Algorithms. Authors are very much encouraged submitting new or modified cutting edge original algorithms or application in academia and industrial exercises and practices.

Recommended Topics
Topics to be discussed in this special issue include (but are not limited to) the following:

  • Particle swarm optimization (PSO)
  • Ant colony optimization (ACO)
  • Artificial bee colony (ABC)
  • Cuckoo search (CS)
  • Bat algorithm (BA)
  • Bio-inspired computation, and its application in solving real world problems as well as large scale problems in engineering, science, technology, economics, management, finance, industry, humanity and social science


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Bio-inspired optimization algorithms and their applications on or before 24th OCTOBER 2018. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All submissions and inquiries should be directed to the attention of:
Dr. Pandian Vasant
Prof. Igor Litvinchev
Dr. Van Van Huynh

Guest Editors
International Journal of Swarm Intelligence Research (IJSIR)
E-mail: pvasant@gmail.com; igorlitvinchev@gmail.com; huynhvanvan@tdt.edu.vn