{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T17:16:50Z","timestamp":1771003010046,"version":"3.50.1"},"reference-count":14,"publisher":"SAGE Publications","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"published-print":{"date-parts":[[2021,11,1]]},"abstract":"<jats:p>The adaptive quantum particle swarm optimization algorithm based on cloud model and the multi-island genetic algorithm\u00a0[15] have obvious advantages in convergence speed to solve the sensor optimization problem, and can effectively achieve global optimization. Due to the installation of sensors and actuators, the electromechanical coupling coefficient of intelligent structures is changed, which affects the vibration energy of structures. In this paper, the reserved energy index of structural vibration control system is taken as the objective optimization function. The position, number, length and control gain of sensors and actuators of active vibration control system are optimized. The adaptive Quantum-behaved Particle Swarm Optimization algorithm in cloud model(CMQPSO) is used as the optimization strategy, and the cantilever beam is taken as an example. This approach is verified its effectiveness and feasibility. It is found that excellent optimization results are obtained.<\/jats:p>","DOI":"10.3233\/jcm-215039","type":"journal-article","created":{"date-parts":[[2021,6,4]],"date-time":"2021-06-04T12:03:20Z","timestamp":1622808200000},"page":"1433-1440","source":"Crossref","is-referenced-by-count":0,"title":["Research of active vibration control optimal disposition based on CMQPSO"],"prefix":"10.1177","volume":"21","author":[{"given":"Xiangzhong","family":"Meng","sequence":"first","affiliation":[]},{"given":"Ying","family":"Ma","sequence":"additional","affiliation":[]},{"given":"Qiang","family":"Guo","sequence":"additional","affiliation":[]}],"member":"179","reference":[{"issue":"1","key":"10.3233\/JCM-215039_ref1","first-page":"74","article-title":"Research of active vibration control optimization based on genetic algorithm","volume":"16","author":"Meng","year":"2008","journal-title":"Computer Measurement & Control"},{"key":"10.3233\/JCM-215039_ref2","doi-asserted-by":"crossref","unstructured":"K. Le, J.Q. Xing, J.T. Zhang, X.Z. Xu, M.F. Wu and K.Q. Zhao, Application of a Cloud Model-Set Pair Analysis in Efficacy Assessment for Diabetic Ulcers, Evidence-Based Complementary and Alternative Medicine, 2019.","DOI":"10.1155\/2019\/8450397"},{"issue":"19","key":"10.3233\/JCM-215039_ref3","first-page":"68","article-title":"Research on improvement of adaptive ant colony algorithm based on cloud model","volume":"52","author":"Liu","year":"2016","journal-title":"Computer Engineering and Application"},{"issue":"6","key":"10.3233\/JCM-215039_ref4","first-page":"29","article-title":"Adaptive quantum particle swarm optimization algorithm based on normal cloud model","volume":"40","author":"Yu","year":"2019","journal-title":"Joural of Jishou University"},{"issue":"2","key":"10.3233\/JCM-215039_ref5","first-page":"228","article-title":"Quantum-behaved particle swarm algorithm with self-adapting adjustment of inertia weight","volume":"46","author":"Huang","year":"2012","journal-title":"Journal of Shanghai Jiaotong University"},{"issue":"20","key":"10.3233\/JCM-215039_ref6","first-page":"34","article-title":"Improved quantum particle swarm optimization algorithm and its application","volume":"47","author":"Xu","year":"2011","journal-title":"Computer Engineering and Applications"},{"issue":"5","key":"10.3233\/JCM-215039_ref7","first-page":"221","article-title":"Parallel adaptive immune quantum-behaved particle swarm optimization algorithm","volume":"37","author":"Li","year":"2011","journal-title":"Computer Engineering"},{"key":"10.3233\/JCM-215039_ref8","unstructured":"J. Sun, B. Feng and W.B. Xu, Praticle swarm optimization with particles having quantum behavior[C], Proceedings of the 2004 Congress on Evolutionary Computation, Portland: IEEE Press, 2004, pp. 325\u2013331."},{"issue":"8","key":"10.3233\/JCM-215039_ref9","first-page":"127","article-title":"Chaos quantum particle swarm optimization algorithm with self-adapting adjustment of inertia weight","volume":"21","author":"Li","year":"2012","journal-title":"Computer Systems & Application"},{"issue":"8","key":"10.3233\/JCM-215039_ref10","first-page":"64","article-title":"Adaptive mutation Quantum-Behaved Particle Swarm Optimization algorithm based on normal cloud model","volume":"24","author":"Guan","year":"2016","journal-title":"Electronic Design Engineering"},{"issue":"10","key":"10.3233\/JCM-215039_ref12","first-page":"99","article-title":"Attribute reduction method based on cloud quantum PSO","volume":"54","author":"Chang","year":"2018","journal-title":"Computer Engineering and Application"},{"issue":"6","key":"10.3233\/JCM-215039_ref13","doi-asserted-by":"crossref","first-page":"3686","DOI":"10.7498\/aps.59.3686","article-title":"Convergence analysis of quantum-behaved particle swarm optimization algorithm and study on its control parameter","volume":"59","author":"Fang","year":"2012","journal-title":"Acta Physica Sinica"},{"issue":"28","key":"10.3233\/JCM-215039_ref15","first-page":"62","article-title":"Optimal placement of vibration control sensors based on multi-island genetic algorithm","volume":"3","author":"Shi","year":"2008","journal-title":"Journal of Vibration, Measurement & Diagnosis"},{"key":"10.3233\/JCM-215039_ref16","unstructured":"Y.F. Li, Hybrid particle swarm optimization support vector machine circuit fault diagnosis [D]. Hunan University, 2018."}],"container-title":["Journal of Computational Methods in Sciences and Engineering"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JCM-215039","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T16:31:13Z","timestamp":1771000273000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JCM-215039"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,1]]},"references-count":14,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.3233\/jcm-215039","relation":{},"ISSN":["1472-7978","1875-8983"],"issn-type":[{"value":"1472-7978","type":"print"},{"value":"1875-8983","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,1]]}}}