Ahmed Y. Hamed¹, Monagi H. Alkinani², M. R. Hassan^3,*

Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1201-1216, 2020, DOI:10.32604/iasc.2020.012663 - 24 December 2020

Abstract Many applications require to send information from a source node to multiple destinations nodes. To support these applications, the paper presents a multi-objective based genetic algorithm, which is used in the construction of the multicast tree for data transmission in a computer network. The proposed algorithm simultaneously optimizes total weights (cost, delay, and hop) of the multicast tree. Experimental results prove that the proposed algorithm outperforms a recently published Multi-objective Multicast Algorithm specially designed for solving the multicast routing problem. Also, the proposed approach has been applied to ten-node and twenty-node network to illustrate its More >

Juanjuan Wang, Yajuan Jia^*, Jiangping Nan

FDMP-Fluid Dynamics & Materials Processing, Vol.16, No.6, pp. 1161-1175, 2020, DOI:10.32604/fdmp.2020.010328 - 17 December 2020

Abstract The present study aims at improving the accuracy of weather forecast by providing useful information on the behavior and response of a sounding temperature sensor. A hybrid approach relying on Computational Fluid Dynamics and a genetic algorithm (GA) is used to simulate the system represented by the bead thermistor and the surrounding air. In particular, the influence of different lead angles, sensor lead length, and lead number is considered. The results have shown that when the length of the lead wire of the bead thermistor is increased, the radiation temperature rise is reduced; when the More >

Junhui Wang¹, Wanzi Yan¹, Zhijun Wan^1,*, Yi Wang^2,*, Jiakun Lv¹, Aiping Zhou³

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 1135-1157, 2020, DOI:10.32604/cmes.2020.014313 - 15 December 2020

Abstract Precise recovery of Coalbed Methane (CBM) based on transparent reconstruction of geological conditions is a branch of intelligent mining. The process of permeability reconstruction, ranging from data perception to real-time data visualization, is applicable to disaster risk warning and intelligent decision-making on gas drainage. In this study, a machine learning method integrating the Random Forest (RF) and the Genetic Algorithm (GA) was established for permeability prediction in the Xishan Coalfield based on Uniaxial Compressive Strength (UCS), effective stress, temperature and gas pressure. A total of 50 sets of data collected by a self-developed apparatus were… More >

Amin Ranjbar¹, Amir Abolzafl Suratgar^1,*, Saeed Shiry Ghidary², Jafar Milimonfared³

Sound & Vibration, Vol.54, No.4, pp. 257-267, 2020, DOI:10.32604/sv.2020.05055 - 25 November 2020

Abstract This paper proposes an efficient learning based approach to detect the faults of an industrial oil pump. The proposed method uses the wavelet transform and genetic algorithm (GA) ensemble for an optimal feature extraction procedure. Optimal features, which are dominated through this method, can remarkably represent the mechanical faults in the damaged machine. For the aim of condition monitoring, we considered five common types of malfunctions such as casing distortion, cavitation, looseness, misalignment, and unbalanced mass that occur during the machine operation. The proposed technique can determine optimal wavelet parameters and suitable statistical functions to More >

Zaoyu Wei^1,*, Jiaqi Wang², Xueqi Shen¹, Qun Luo¹

Journal of Information Hiding and Privacy Protection, Vol.2, No.1, pp. 35-45, 2020, DOI:10.32604/jihpp.2020.010331 - 15 October 2020

Abstract Smart contract has greatly improved the services and capabilities of blockchain, but it has become the weakest link of blockchain security because of its code nature. Therefore, efficient vulnerability detection of smart contract is the key to ensure the security of blockchain system. Oriented to Ethereum smart contract, the study solves the problems of redundant input and low coverage in the smart contract fuzz. In this paper, a taint analysis method based on EVM is proposed to reduce the invalid input, a dangerous operation database is designed to identify the dangerous input, and genetic algorithm More >

Yanan Zhang^1,*, Lin Ouyang², Qinqin Li², Haichen Ju²

Journal on Big Data, Vol.2, No.3, pp. 125-133, 2020, DOI:10.32604/jbd.2020.012879 - 13 October 2020

Abstract Under the traditional dynamic model, the conventional method for solving the rotation angle of a rigid body is to use the fixed-axis rotation law of the rigid body, but the known rotation shaft position must be used as a prerequisite. In practical work, for the rotation of a rigid body under multiple forces, solving the shaft is often a difficult problem. In this paper, we consider the rigid body of the disc is subjected to the force of uneven magnitude from multiple angles, the position of the rotating shaft is obtained by iterative inversion through… More >

S. Jerald Nirmal Kumar^1,*, S. Ravimaran², M. M. Gowthul Alam³

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 671-697, 2020, DOI:10.32604/cmes.2020.09361 - 12 October 2020

Abstract Nowadays, succeeding safe communication and protection-sensitive data from unauthorized access above public networks are the main worries in cloud servers. Hence, to secure both data and keys ensuring secured data storage and access, our proposed work designs a Novel Quantum Key Distribution (QKD) relying upon a non-commutative encryption framework. It makes use of a Novel Quantum Key Distribution approach, which guarantees high level secured data transmission. Along with this, a shared secret is generated using Diffie Hellman (DH) to certify secured key generation at reduced time complexity. Moreover, a non-commutative approach is used, which effectively More >

Soukaina Mjahed^1,*, Khadija Bouzaachane¹, Ahmad Taher Azar^2,3, Salah El Hadaj¹, Said Raghay¹

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 459-494, 2020, DOI:10.32604/cmes.2020.010791 - 12 October 2020

Abstract This paper focuses on the unsupervised detection of the Higgs boson particle using the most informative features and variables which characterize the “Higgs machine learning challenge 2014” data set. This unsupervised detection goes in this paper analysis through 4 steps: (1) selection of the most informative features from the considered data; (2) definition of the number of clusters based on the elbow criterion. The experimental results showed that the optimal number of clusters that group the considered data in an unsupervised manner corresponds to 2 clusters; (3) proposition of a new approach for hybridization of… More >

U. Venkateshkumar^1,*, S. Ramakrishnan²

Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 817-830, 2020, DOI:10.32604/iasc.2020.010116

Abstract A hybrid form of the genetic algorithm and the modified K-Means cluster algorithm forms as a Gencluster to detect a spectrum hole among n-number of primary users (PUs) is present in the cooperative spectrum sensing model. The fusion center (FC), applies the genetic algorithm to identify the best chromosome, which contains many PUs cluster centers and by applying the modified K-Means cluster algorithm identifies the cluster with the PU vacant spectrum showing high accuracy, and maximum probability of detection with minimum false alarm rates are achieved. The graphical representation of the performance metric of the More >

Hong Zhu^1,2,*

Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 741-748, 2020, DOI:10.32604/iasc.2020.010108

Abstract In this paper, a human resource allocation method based on the multi-objective hybrid genetic algorithm is proposed, which uses the multi-stage decision model to resolve the problem. A task decision is the result of an interaction under a set of conditions. There are some available decisions in each stage, and it is easy to calculate their immediate effects. In order to give a set of optimal solutions with limited submissions, a multi-objective hybrid genetic algorithm is proposed to solve the combinatorial optimization problems, i.e. using the multiobjective hybrid genetic algorithm to find feasible solutions at… More >