An effective regenerative braking strategy based on the combination algorithm of particle swarm optimization and ant colony optimization for electrical vehicle

Research article (2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), 2019) · cited 13× · AI/ML
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An effective regenerative braking strategy based on the combination algorithm of particle swarm optimization and ant colony optimization for electrical vehicle

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An effective regenerative braking strategy based on the combination algorithm of particle swarm optimization and ant colony optimization for electrical vehicle is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). An effective regenerative braking strategy based on the combination algorithm of particle swarm optimization and ant colony optimization for electrical vehicle. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-effective-regenerative-braking-strategy-based-on-the-combination-algorithm-of-particle-swarm-optimization-and-ant-col
MLA “An effective regenerative braking strategy based on the combination algorithm of particle swarm optimization and ant colony optimization for electrical vehicle.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-effective-regenerative-braking-strategy-based-on-the-combination-algorithm-of-particle-swarm-optimization-and-ant-col.
BibTeX @misc{4ortxyz_an-effective-regenerative-braking-strategy-based-on-the-combination-algorithm-of-particle-swarm-optimization-and-ant-col_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An effective regenerative braking strategy based on the combination algorithm of particle swarm optimization and ant colony optimization for electrical vehicle}}, year = {2026}, url = {https://4ort.xyz/entity/an-effective-regenerative-braking-strategy-based-on-the-combination-algorithm-of-particle-swarm-optimization-and-ant-col}, note = {Accessed: 2026-05-24}}
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