Linguo Li^{1, 2}, Lijuan Sun¹, Jian Guo¹, Shujing Li^{2, *}, Ping Jiang³

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 761-775, 2020, DOI:10.32604/cmc.2020.010158 - 23 July 2020

Abstract As an indispensable task in crop protection, the detection of crop diseases directly impacts the income of farmers. To address the problems of low crop-disease identification precision and detection abilities, a new method of detection is proposed based on improved genetic algorithm and extreme learning machine. Taking five different typical diseases with common crops as the objects, this method first preprocesses the images of crops and selects the optimal features for fusion. Then, it builds a model of crop disease identification for extreme learning machine, introduces the hill-climbing algorithm to improve the traditional genetic algorithm, More >

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

Journal of Quantum Computing, Vol.2, No.1, pp. 11-24, 2020, DOI:10.32604/jqc.2020.010815 - 28 May 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 >

Laith Sawaqed¹, Khaled S. Hatamleh^1,2, Mohammad A. Jaradat^1,2, Qais Khasawneh^1,3

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 507-515, 2018, DOI:10.31209/2018.100000039

Abstract Over the past few years, there has been a growing demand to develop efficient precision mechanisms for fine moving applications. Therefore, several piezoelectric driven mechanisms have been proposed for such applications. In this work an optimal synthesis of a four-bar mechanism with three PEAs is proposed. Two evolutionary multi-objective Genetic Algorithms (GAs) are formulated and applied; A Genetic Algorithm Synthesis method (GAS) is first used to obtain a synthesis solution for the mechanism regardless of power consumption. Then another Genetic Algorithm Minimum Power Synthesis method (GAMPS) is used to obtain the synthesis solution of minimum More >

S. M. Mousavi^a, M. Zandieh^b

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 9-16, 2018, DOI:10.1080/10798587.2016.1261956

Abstract This paper considers the problem of scheduling n independent jobs in g-stage hybrid flow shop environment. To address the realistic assumptions of the proposed problem, two additional traits were added to the scheduling problem. These include setup times, and the consideration of maximum completion time together with total tardiness as objective function. The problem is to determine a schedule that minimizes a convex combination of objectives. A procedure based on hybrid the simulated annealing; genetic algorithm and local search so-called HSA-GA-LS are proposed to handle this problem approximately. The performance of the proposed algorithm is More >