Guest Editors
Dr. Prateek Agrawal, Lovely Professional University, India.
Dr. Charu Gupta, Bhagwan Parshuram Institute of Technology, GGS-Indraprastha University, India.
Dr. Deepali Virmani, Bhagwan Parshuram Institute of Technology, GGS-Indraprastha University, India.
Prof. Vishu Madaan, Lovely professional University, India.
Summary
In today's era, emerging technology uses the intelligence to perform specialized tasks from the observation it makes from the environment. The task requires intelligence of machines to reach new heights of technical and conceptual advancement Further, this advancement is incomplete without exploring the concepts and advances of Computational Intelligence (CI). Intelligence in computational systems has given rise to emerging technologies which are used for better living.
CI is an essential factor in Intelligence 4.0 which includes approaches and methods. It consists of theories, theorems, proofs, axioms, applications and comparisons of computationally motivated paradigms. It provides computational solutions to multi-domain problems and applications which deal with the datasets ranging from database to exascale, homogeneity to heterogeneity, variety to veracity.
CI gives the tools and techniques for re-living exploratory perceptions covering the complete spectrum of application and development of methods used in various expert systems. In today's era, when Exabytes of data is being generated on a daily basis, there is a great need of some intelligent methods and tools that would be robust and compatible to analyse and extract the meaningful information from them and help the users in making some fruitful and quick decisions.
The benefit of using CI tools and techniques is the elevation of real dynamic problems to automation which not only increases productivity, enhances the social and living structure of the society and people at large.
In view of these factors CI, its concepts, applications and meta-heuristics find great applications in solving real life problems. The aim of this issue is to record and disseminate the contributions from researchers, academicians and industry experts in the CI domain. The future of CI can further be extended to nature inspired computational intelligent tools and techniques for finding efficient solutions to real time problems with much ease and understanding.
Scope of the proposed special issue is as follows (not limited to):
Artificial Intelligence-based Emerging technologies
Intelligent healthcare applications
Machine learning models
Deep learning applications
Natural language processing
Soft Computing applications
Industry 4.0
Disruptive Technologies
Privacy challenges in Social networks
Social Network and Data Analytics
Recommender systems Applications in Social Networks
AI applications in smart cities
Internet of everything
Intelligent sustainable development
Explainable AI
Decentralized blockchain methods
Trust based communication
Expert systems
Keywords
Machine learning, deep learning, image processing, soft computing, internet of things, natural language processing
Published Papers
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Open Access
ARTICLE
Coronavirus Decision-Making Based on a Locally -Generalized Closed Set
M. A. El Safty, S. A. Alblowi, Yahya Almalki, M. El Sayed
Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 483-498, 2022, DOI:10.32604/iasc.2022.021581
（This article belongs to this Special Issue:
Intelligence 4.0: Concepts and Advances in Computational Intelligence)
Abstract Real-world applications now deal with a massive amount of data, and information about the world is inaccurate, incomplete, or uncertain. Therefore, we present in our paper a proposed model for solving problems. This model is based on the class of locally generalized closed sets, namely, locally simply* alpha generalized closed* sets and locally simply* alpha generalized closed** sets (briefly, -sets and -sets), based on simply* alpha open set. We also introduce various concepts of their properties and their relationship with other types, and we are studying several of their properties. Finally, we apply the concept of the simply* alpha open…
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Open Access
ARTICLE
Deriving Driver Behavioral Pattern Analysis and Performance Using Neural Network Approaches
Meenakshi Malik, Rainu Nandal, Surjeet Dalal, Vivek Jalglan, Dac-Nhuong Le
Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 87-99, 2022, DOI:10.32604/iasc.2022.020249
（This article belongs to this Special Issue:
Intelligence 4.0: Concepts and Advances in Computational Intelligence)
Abstract It has been observed that driver behavior has a direct and considerable impact upon factors like fuel consumption, environmentally harmful emissions, and public safety, making it a key consideration of further research in order to monitor and control such related hazards. This has fueled our decision to conduct a study in order to arrive at an efficient way of analyzing the various parameters of driver behavior and find ways and means of positively impacting such behavior. It has been ascertained that such behavioral patterns can significantly impact the analysis of traffic-related conditions and outcomes. In such cases, the specific vehicular…
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Open Access
ARTICLE
Early Detection of Alzheimer’s Disease Using Graph Signal Processing and Deep Learning
Himanshu Padole, S. D. Joshi, Tapan K. Gandhi
Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1655-1669, 2022, DOI:10.32604/iasc.2022.021310
（This article belongs to this Special Issue:
Intelligence 4.0: Concepts and Advances in Computational Intelligence)
Abstract Many methods have been proposed in the literature for diagnosis of Alzheimer's disease (AD) in the early stages, among which the graph-based methods have been more popular, because of their capability to utilize the relational information among different brain regions. Here, we design a novel graph signal processing based integrated AD detection model using multimodal deep learning that simultaneously utilizes both the static and the dynamic brain connectivity based features extracted from resting-state fMRI (rs-fMRI) data to detect AD in the early stages. First, our earlier proposed state-space model (SSM) based graph connectivity dynamics characterization method is used to design…
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Open Access
ARTICLE
H-infinity Controller Based Disturbance Rejection in Continuous Stirred-Tank Reactor
Sikander Hans, Smarajit Ghosh
Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 29-41, 2022, DOI:10.32604/iasc.2022.019525
（This article belongs to this Special Issue:
Intelligence 4.0: Concepts and Advances in Computational Intelligence)
Abstract This paper offers an H-infinity (H∞) controller-based disturbance rejection along with the utilization of the water wave optimization (WWO) algorithm. H∞ controller is used to synthesize the guaranteed performance of certain applications as well as it provides maximum gain at any situation. The proposed work focuses on the conflicts of continuous stirred-tank reactor (CSTR) such as variation in temperature and product concentration. The elimination of these issues is performed with the help of the WWO algorithm along with the controller operation. In general, the algorithmic framework of WWO algorithm is simple, and easy to implement with a small-size population and…
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Open Access
ARTICLE
Deep Learning-Based Skin Lesion Diagnosis Model Using Dermoscopic Images
G. Reshma, Chiai Al-Atroshi, Vinay Kumar Nassa, B.T. Geetha, Gurram Sunitha, Mohammad Gouse Galety, S. Neelakandan
Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 621-634, 2022, DOI:10.32604/iasc.2022.019117
（This article belongs to this Special Issue:
Intelligence 4.0: Concepts and Advances in Computational Intelligence)
Abstract In recent years, intelligent automation in the healthcare sector becomes more familiar due to the integration of artificial intelligence (AI) techniques. Intelligent healthcare systems assist in making better decisions, which further enable the patient to provide improved medical services. At the same time, skin lesion is a deadly disease that affects people of all age groups. Skin lesion segmentation and classification play a vital part in the earlier and precise skin cancer diagnosis by intelligent systems. However, the automated diagnosis of skin lesions in dermoscopic images is challenging because of the problems such as artifacts (hair, gel bubble, ruler marker),…
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Open Access
ARTICLE
Fault-Tolerant Communication Induced Checkpointing and Recovery Protocol Using IoT
Neha Malhotra, Manju Bala
Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 945-960, 2021, DOI:10.32604/iasc.2021.019082
（This article belongs to this Special Issue:
Intelligence 4.0: Concepts and Advances in Computational Intelligence)
Abstract In mobile computing systems, nodes in the network take checkpoints to survive failures. Certain characteristics of mobile computing systems such as mobility, low bandwidth, disconnection, low power consumption, and limited memory make these systems more prone to failures. In this paper, a novel minimum process communication-induced checkpointing algorithm that makes full use of the computation ability and implementation of effective stable storage in a mobile computing system is proposed. The said approach initiates by taking spontaneous checkpoints by each node in phase 1 using a logistic function that is specifically used to estimate the time interval between two checkpoints and…
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