Decentralized Microenvironment-Based Particle Swarm Optimization Algorithm for Insect-Intelligent Building Platform
-д хадгалсан:
| -д хэвлэсэн: | Buildings vol. 15, no. 11 (2025), p. 1778 |
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| Үндсэн зохиолч: | |
| Бусад зохиолчид: | , , , |
| Хэвлэсэн: |
MDPI AG
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| Нөхцлүүд: | |
| Онлайн хандалт: | Citation/Abstract Full Text + Graphics Full Text - PDF |
| Шошгууд: |
Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!
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MARC
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| 003 | UK-CbPIL | ||
| 022 | |a 2075-5309 | ||
| 024 | 7 | |a 10.3390/buildings15111778 |2 doi | |
| 035 | |a 3217719990 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231437 |2 nlm | ||
| 100 | 1 | |a Zhang, Zhenya |u Anhui Province Key Laboratory of Intelligent Building & Building Energy Saving, Anhui Jianzhu University, Hefei 230022, China; zzychm@ustc.edu.cn | |
| 245 | 1 | |a Decentralized Microenvironment-Based Particle Swarm Optimization Algorithm for Insect-Intelligent Building Platform | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Information processing and control tasks in each unit within a building are typically completed internally, and information processing within a building naturally exhibits distributed characteristics. The insect-intelligent building platform is an intelligent building platform, and the concept of an insect-intelligent building platform adapts to the distributed processing requirements of building information, achieving features such as self-organization and self-adaptation of the intelligent building platform. The microenvironment network serves as a fundamental network that supports the implementation of an insect-intelligent building platform. Update mechanisms for the velocity and position of particles for PSO in the microenvironment are given. This paper also proposes a Microenvironment-based Particle Swarm Optimization (MPSO) algorithm with those update mechanisms to quickly solve optimization problems using PSO under a microenvironment network. Experimental results show that, within microenvironment networks, both synchronous and asynchronous implementations of MPSO algorithms can solve optimization problems faster than the PSO algorithm while maintaining a precision similar to that of the PSO algorithm. | |
| 653 | |a Particle swarm optimization | ||
| 653 | |a Control tasks | ||
| 653 | |a Data processing | ||
| 653 | |a Collaboration | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Algorithms | ||
| 653 | |a Building automation | ||
| 653 | |a Smart buildings | ||
| 653 | |a Information processing | ||
| 653 | |a Microenvironments | ||
| 653 | |a Insects | ||
| 653 | |a Optimization algorithms | ||
| 653 | |a Distributed processing | ||
| 700 | 1 | |a Xu, Shaojie |u School of Electronic and Information Engineering, Anhui Jianzhu University, Hefei 230022, China; 202333105164@stu.ahjzu.edu.cn (S.X.); wangping@ahjzu.edu.cn (P.W.) | |
| 700 | 1 | |a Wang, Ping |u School of Electronic and Information Engineering, Anhui Jianzhu University, Hefei 230022, China; 202333105164@stu.ahjzu.edu.cn (S.X.); wangping@ahjzu.edu.cn (P.W.) | |
| 700 | 1 | |a Cheng, Hongmei |u School of Economics and Management, Anhui Jianzhu University, Hefei 230022, China | |
| 700 | 1 | |a Zhang, Shuguang |u Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei 230026, China; sgzhang@ustc.edu.cn | |
| 773 | 0 | |t Buildings |g vol. 15, no. 11 (2025), p. 1778 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3217719990/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3217719990/fulltextwithgraphics/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3217719990/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |