Author(s)

Weipeng Xu ¹, Jiakang Ma ²

Affiliation(s)

¹ School of Economics and Management, Tiangong University, Tianjin, 300387, China
² School of Traffic & Transportation Engineering, Central South University, Changsha, 410083, China

Corresponding Author

Weipeng Xu

ABSTRACT

Accurate temperature forecasting is crucial for fields like meteorology, agriculture, energy management, and urban planning. Traditional models often fail to capture complex nonlinear patterns in temperature data. The BP neural network, while powerful, faces challenges such as local minima and network structure selection. To address these, this paper integrate Genetic Algorithms (GA) with BP neural networks using the NEAT algorithm, which evolves network topologies and weights. This hybrid GA-BP: NEAT model enhances prediction accuracy and stability by avoiding local minima and optimizing network complexity. Experimental results show significant improvements in forecasting nonlinear time series data, offering valuable insights for various applications.

KEYWORDS

Temperature Prediction, Back Propagation Neural Network, NEAT Algorithm, Data Preprocessing, Model Optimization

CITE THIS PAPER

Weipeng Xu, Jiakang Ma, Temperature Prediction Based on NEAT-Optimized GA-BP Neural Network. Automation and Machine Learning (2024) Vol. 5: 25-32. DOI: http://dx.doi.org/10.23977/autml.2024.050204.

REFERENCES

[1] Jianan Liu. Research on Short-term Climate Prediction in China Based on Machine Learning Methods [D]. Nanjing University of Information Science & Technology, 2023. 
[2] Zitong Yu. Stock Selection Model Based on BP Neural Network Optimized by Genetic Algorithm [D]. Dongbei University of Finance and Economics, 2022. 
[3] Pang P ,Zheng J ,Zhao Y , et al. Thermal-vibration correlation study for high-temperature superconducting maglev intelligent monitoring based on back propagation neural network analysis[J].Superconductor Science and Technology, 2024, 37(2).
[4] Yewei Cheng. Research on Prediction of Coal and Gas Outbursts Based on SKPCA and NEAT Algorithms [D]. Liaoning Technical University, 2021. 
[5] Shuxian Yang. Research on Seasonal Prediction of Summer Precipitation and Temperature in the Middle and Lower Reaches of the Yangtze River Based on Deep Learning Methods [D]. Nanjing University of Information Science & Technology, 2023.

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