Shuangying Liu¹, Weidong Zhang^2,*

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 569-575, 2020, DOI:10.32604/iasc.2020.013935

Abstract The constant development of computer technology has greatly facilitated our life. In the past, the agricultural products trade and agricultural products business model were an offline development, through face-to-face transactions. However, with the continuous application of Internet technology, we also have a new exploration on the e-commerce path of agricultural products. The fuzzy neural network algorithm was used to study the electronic commerce path of agricultural products and helped us to carry out the exploration computation of the electronic commerce path of agricultural products. And good calculation results have been obtained. Through our testing of More >

L. Ezhilarasi^1,*, A.P. Shanthi², V. Uma Maheswari¹

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 465-478, 2020, DOI:10.32604/iasc.2020.013923

Abstract Development of new Artificial Intelligence related data analy sis methodologies w ith rev olutionary information technology has made a radical change in prediction, forecasting, and decision making for real-w orld data. The challenge arises w hen the real w orld dataset consisting of v oluminous data is uncertain. The rough set is a mathematical formalism that has emerged significantly for uncertain datasets. It represents the know ledge of the datasets as decision rules. It does not need any metadata. The rules are used to predict or classify unseen ex amples. The objectiv e of this… More >

Abid Nisar¹, Waheed Iqbal^1,*, Fawaz Bokhari¹, Faisal Bukhari¹, Khaled Almustafa²

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 353-365, 2020, DOI:10.31209/2019.100000159

Abstract The adaptive resource provisioning of cloud-hosted applications is enabled to provide a better quality of services to the users of applications. Most of the cloud-hosted applications follow the multi-tier architecture model. However, it is challenging to adaptively provision the resources of multi-tier applications. In this paper, we propose an auto-scaling method to dynamically scale resources for multi-tier web applications. The proposed method exploits the horizontal scaling at the web server tier and vertical scaling at the database tier dynamically to maintain response time guarantees. We evaluated our proposed method on Amazon Web Services using a More >

Parvathavarthini S^1,*, Karthikeyani Visalakshi N², Shanthi S³, Madhan Mohan J⁴

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 253-260, 2020, DOI:10.31209/2019.100000155

Abstract Intuitionistic fuzzy clustering allows the uncertainties in data to be represented more precisely. Medical data usually possess a high degree of uncertainty and serve as the right candidate to be represented as Intuitionistic fuzzy sets. However, the selection of initial centroids plays a crucial role in determining the resulting cluster structure. Crow search algorithm is hybridized with Intuitionistic fuzzy C-means to attain better results than the existing hybrid algorithms. Still, the performance of the algorithm needs improvement with respect to the objective function and cluster indices especially with internal indices. In order to address these More >

Karim Hammoudi^1,2,*, Adnane Cabani³, Halim Benhabiles⁴, Mahmoud Melkemi^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1049-1059, 2020, DOI:10.32604/cmes.2020.011663 - 21 August 2020

Abstract In a context of a virus that is transmissive by sputtering, wearing masks appear necessary to protect the wearer and to limit the propagation of the disease. Currently, we are facing the 2019–2020 coronavirus pandemic. Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu. The symptom of COVID-19 was reported first in China and very quickly spreads to the rest of the world. The COVID-19 contagiousness is known to be high by comparison with the flu. In this paper, we propose a design of a mobile application for permitting… More >

Inzamam Mashood Nasir¹, Muhammad Attique Khan^1,*, Majed Alhaisoni², Tanzila Saba³, Amjad Rehman³, Tassawar Iqbal⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1017-1033, 2020, DOI:10.32604/cmes.2020.010943 - 21 August 2020

Abstract Comic character detection is becoming an exciting and growing research area in the domain of machine learning. In this regard, recently, many methods are proposed to provide adequate performance. However, most of these methods utilized the custom datasets, containing a few hundred images and fewer classes, to evaluate the performances of their models without comparing it, with some standard datasets. This article takes advantage of utilizing a standard publicly dataset taken from a competition, and proposes a generic data balancing technique for imbalanced dataset to enhance and enable the in-depth training of the CNN. In More >

Yingjun Wang^1,*, Zhenpei Wang², Xiaowei Deng³, David J. Benson⁴, Damiano Pasini⁵, Shuting Wang⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 783-785, 2020, DOI:10.32604/cmes.2020.013234 - 21 August 2020

Abstract This article has no abstract. More >

Kiranbir Kaur^{1, *}, Sandeep Sharma¹, Karanjeet Singh Kahlon²

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1625-1647, 2020, DOI:10.32604/cmc.2020.011535 - 20 August 2020

Abstract Vendor lock-in can occur at any layer of the cloud stack-Infrastructure, Platform, and Software-as-a-service. This paper covers the vendor lock-in issue at Platform as a Service (PaaS) level where applications can be created, deployed, and managed without worrying about the underlying infrastructure. These applications and their persisted data on one PaaS provider are not easy to port to another provider. To overcome this issue, we propose a middleware to abstract and make the database services as cloud-agnostic. The middleware supports several SQL and NoSQL data stores that can be hosted and ported among disparate PaaS… More >

Muhammad Abdullah^1,*, Saad Ahmad Khan¹, Mamdouh Alenez², Khaled Almustafa³, Waheed Iqbal¹

Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 13-25, 2020, DOI:10.31209/2018.100000047

Abstract An efficient placement of virtual machines (VMs) in a cloud datacenter is important to maximize the utilization of infrastructure. Most of the existing work maximises the number of VMs to place on a minimum number of physical machines (PMs) to reduce energy consumption. Recently, big data applications become popular which are mostly hosted on cloud datacenters. Big data applications are deployed on multiple VMs and considered data and communication intensive applications. These applications can consume most of the datacenter bandwidth if VMs do not place close to each other. In this paper, we investigate the More >

Qinqin Fan^1,*, Yilian Zhang², Zhihuan Wang¹

Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 1-12, 2020, DOI:10.31209/2018.100000042

Abstract Weak global exploration capability is one of the primary drawbacks in teaching learning based optimization (TLBO). To enhance the search capability of TLBO, an improved TLBO (ITLBO) is introduced in this study. In ITLBO, a uniform random number is replaced by a normal random number, and a weighted average position of the current population is chosen as the other teacher. The performance of ITLBO is compared with that of five meta-heuristic algorithms on a well-known test suite. Results demonstrate that the average performance of ITLBO is superior to that of the compared algorithms. Finally, ITLBO More >