Huaixi Xing¹, Yu Zhao¹, Yuhui Zhang¹, You Chen^{1, *}

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2295-2308, 2020, DOI:10.32604/cmc.2020.011858

Abstract Aiming at the yaw problem caused by inertial navigation system errors accumulation during the navigation of an intelligent aircraft, a three-dimensional trajectory planning method based on the particle swarm optimization-A star (PSO-A*) algorithm is designed. Firstly, an environment model for aircraft error correction is established, and the trajectory is discretized to calculate the positioning error. Next, the positioning error is corrected at many preset trajectory points. The shortest trajectory and the fewest correction times are regarded as optimization goals to improve the heuristic function of A star (A*) algorithm. Finally, the index weights are continuously optimized by the particle swarm… More >

Meera Sharma¹, H. Pham², V.B. Singh³

Computer Systems Science and Engineering, Vol.34, No.1, pp. 33-46, 2019, DOI:10.32604/csse.2019.34.033

Abstract In Open Source Software (OSS), users report different issues on issues tracking systems. Due to time constraint, it is not possible for developers to resolve all the issues in the current release. The leftover issues which are not addressed in the current release are added in the next release issue content. Fixing of issues result in code changes that can be quantified with a measure known as complexity of code changes or entropy. We have developed a 2-dimensional entropy based mathematical model to determine the leftover issues of different releases of five Apache open source products. A model for release… More >

Tairan Hu¹, Tianyang Zhou¹, Yichao Zang^{1, *}, Qingxian Wang¹, Hang Li²

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1795-1807, 2020, DOI:10.32604/cmc.2020.011071

Abstract With serious cybersecurity situations and frequent network attacks, the demands for automated pentests continue to increase, and the key issue lies in attack planning. Considering the limited viewpoint of the attacker, attack planning under uncertainty is more suitable and practical for pentesting than is the traditional planning approach, but it also poses some challenges. To address the efficiency problem in uncertainty planning, we propose the APU-D* Lite algorithm in this paper. First, the pentest framework is mapped to the planning problem with the Planning Domain Definition Language (PDDL). Next, we develop the pentest information graph to organize network information and… More >

Zhongping Chen¹, Dong Wang^{1, *}, Gang Chen², Yanxi Ren³, Danjie Du⁴

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1781-1793, 2020, DOI:10.32604/cmc.2020.010902

Abstract Due to the unique steering mechanism and driving characteristics of the articulated vehicle, a hybrid path planning method based on the articulated vehicle model is proposed to meet the demand of obstacle avoidance and searching the path back and forth of the articulated vehicle. First, Support Vector Machine (SVM) theory is used to obtain the two-dimensional optimal zero potential curve and the maximum margin, and then, several key points are selected from the optimal zero potential curves by using Longest Accessible Path (LAP) method. Next, the Cubic Bezier (CB) curve is adopted to connect the curve that satisfies the curvature… More >

Vitaliy Mezhuyev^1,*, Yurii Gunchenko², Sergey Shvorov³, Dmitry Chyrchenko³

Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 121-132, 2020, DOI:10.31209/2019.100000133

Abstract The widespread distribution of precision farming systems necessitates improvements in the methods for the control of unmanned harvesting equipment (UHE). While unmanned aerial vehicles (UAVs) provide an effective solution to this problem, there are many challenges in the implementation of technology. This paper considers the problem of identifying optimal routes of UHE movement as a multicriteria evaluation problem, which can be solved by a nonlinear scheme of compromises. The proposed method uses machine learning algorithms and statistical processing of the spectral characteristics obtained from UAV digital images. Developed method minimizes the resources needed for a harvesting campaign and reduces the… More >

Julius Beneoluchi Odili^a, Mohd Nizam Mohmad Kahar^a, A. Noraziah^a,b, M. Zarina^c, Riaz Ul Haq^a

Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 759-769, 2018, DOI:10.1080/10798587.2017.1334370

Abstract This paper carries out a performance analysis of major Nature-inspired Algorithms in solving the benchmark symmetric and asymmetric Traveling Salesman’s Problems (TSP). Knowledge of the workings of the TSP is very useful in strategic management as it provides useful guidance to planners. After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and… More >

Kazim Sari

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 405-412, 2018, DOI:10.1080/10798587.2017.1352258

Abstract Nowadays, there has been a great interest for business enterprises to work together or collaborate in the supply chain. It is thus possible for them to gain a competitive advantage in the marketplace. However, determining the right collaboration strategy is not an easy task. Namely, there are several factors that need to be considered at the same time. In this regard, an expert system based on fuzzy rules is proposed to choose an appropriate collaboration strategy for a given supply chain. To this end, firstly, the factors that are significant for supply chain collaboration are extracted via an extensive review… More >

Li-Hong Juang¹, Shengxiang Zhang²

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 451-458, 2019, DOI:10.31209/2019.100000126

Abstract Intelligent robots are the combination of computer engineering, software engineering, control engineering, electronic engineering, mechanical engineering, and systems design engineering in order to design, and manufacture useful products. In this paper, the author derives some novel computing and algorithm applications on computer vision and image processing and intelligent control and navigation of mobile robots for the intelligent service robot system. In this paper, we proposed an idea of flexible design for a intelligent service robot, which refers to a single robot with a variety of flexure structure. We presented an integrated system for vision-guided finding the person and completing obstacle… More >

Honghao Gao^{1, 2, 5}, Wanqiu Huang^{1, 4}, Xiaoxian Yang³

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 547-559, 2019, DOI:10.31209/2019.100000110

Abstract Path planning is an important topic of research in modern intelligent traffic systems (ITSs). Traditional path planning methods aim to identify the shortest path and recommend this path to the user. However, the shortest path is not always optimal, especially in emergency rescue scenarios. Thus, complex and changeable factors, such as traffic congestion, road construction and traffic accidents, should be considered when planning paths. To address this consideration, the maximum passing probability of a road is considered the optimal condition for path recommendation. In this paper, the traffic network is abstracted as a directed graph. Probabilistic data on traffic flow… More >

Jiping Liu^a,b, Xiaochen Kang^a,*, Chun Dong^a, Fuhao Zhang^a

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 65-77, 2019, DOI:10.31209/2018.100000013

Abstract To guarantee both the efficiency and accuracy of the transportation system, the real-time status should be analyzed to provide a reasonable plan for the near future. This paper proposes a model for simulating the real-world transportation networks by representing the irregular road networks with static and dynamic attributes, and the vehicles as moving agents constrained by the road networks. The all pairs shortest paths (APSP) for the networks are calculated in a real-time manner, and the ever-changing paths can be used for navigating the moving vehicles with real-time positioning devices. In addition, parallel computation is used to accelerate the shortest… More >