An optimized potential formula of the $ m \times n $ apple surface network and its application of potential in path planning

An optimized potential formula for the $ m \times n $ apple surface network has been introduced in this paper. Compared with the original potential formula, this method significantly enhances the efficiency required for rapid and large-scale numerical simulations. Based on the optimized potential function, we proposed a metaheuristic algorithm suitable for apple surface environment path planning. Chebyshev polynomials of the first class were employed to represent the potential function. Subsequently, a fast algorithm for calculating the potential utilizing the first kind of discrete sine transform (DST-I) was devised. We proposed potential formulas for several cases to visually present the distribution of the potential and illustrated them using three-dimensional graphs. We also conducted simulation experiments on the computational efficiency of the original and optimized formulas at different data scales, verifying the superiority of the optimized formulas. These findings provided new perspectives and tools for the computation of resistor networks and the design of path planning algorithms. Experiments were conducted to analyze the efficiency and availability of various techniques for computing potential.

Authors

Institutions

Publication Details

Journal
Electronic Research Archive
Published
2025-01-01
DOI
https://doi.org/10.3934/era.2025083
Citations
1
Primary Topic
Data Management and Algorithms
Type
article
Field-Weighted Citation Impact
1.49
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An optimized potential formula of the $ m \times n $ apple surface network and its application of potential in path planning

Zhaolin Jiang, Yanpeng Zheng, Zhibin Liu, Yangming Xu et al.
1 citations
Electronic Research Archive
Data Management and Algorithms
1.49
article

An optimized potential formula of the $ m \times n $ apple surface network and its application of potential in path planning

Zhaolin Jiang, Yanpeng Zheng, Zhibin Liu, Yangming Xu, Xiaoyu Jiang
article en
1 citations

Abstract

An optimized potential formula for the $ m \times n $ apple surface network has been introduced in this paper. Compared with the original potential formula, this method significantly enhances the efficiency required for rapid and large-scale numerical simulations. Based on the optimized potential function, we proposed a metaheuristic algorithm suitable for apple surface environment path planning. Chebyshev polynomials of the first class were employed to represent the potential function. Subsequently, a fast algorithm for calculating the potential utilizing the first kind of discrete sine transform (DST-I) was devised. We proposed potential formulas for several cases to visually present the distribution of the potential and illustrated them using three-dimensional graphs. We also conducted simulation experiments on the computational efficiency of the original and optimized formulas at different data scales, verifying the superiority of the optimized formulas. These findings provided new perspectives and tools for the computation of resistor networks and the design of path planning algorithms. Experiments were conducted to analyze the efficiency and availability of various techniques for computing potential.

Electronic Research ArchiveVol. 33(3)
Linyi University (CN)
Openalex Percentile: Top 21%
Data Management and Algorithms
1.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

An optimized potential formula of the $ m \times n $ apple surface network and its application of potential in path planning — Zhaolin Jiang, Yanpeng Zheng, et al. · Electronic Research Archive (2025) | TGRS Research Map | TGRS