With the development of economy, environmental problems are becoming more and more prominent, especially the water environment has received extensive attention from the society. As a new type of investment and financing model, the PPP model has obvious advantages, especially in the field of water pollution prevention and control, and has received widespread attention from the society. The purpose of this work is to study the PPP model of water pollution prevention and control engineering based on BP neural network. On the basis of in-depth study of domestic and foreign PPP model literature, combined with relevant successful PPP cases, this paper studies typical cases of water pollution control PPP projects in City A and their corresponding suggestions, identification and demonstration of PPP projects, stages of project implementation and deliver. It is recommended to set up PPP projects of "control units", implement mixed ownership of construction supervision, and adopt the method of "simultaneous projection of cities and counties". The total investment of the project is 726.1945 million yuan, which is mainly used to purchase the fixed assets of the project. Sensitivity analysis of the project shows that if the operating income decreases by 5%, the internal rate of return (IRR) of the total investment will drop to 6.72%, and if the operating cost increases by 5%, the IRR of the project will decrease. The total investment will be reduced to 7.52%.

Jain Rohit. PPP Mode of Water Pollution Prevention and Control Project Based on BP Neural Network. Academic Journal of Environmental Biology (2021), Vol. 2, Issue 3: 47-55. https://doi.org/10.38007/AJEB.2021.020306.

[1] Krasuski K, Wierzbicki D, Jafernik H. Utilization PPP method in aircraft positioning in post-processing mode. Aircraft engineering, 2018, 90(1):202-209.

[2] Kaveh O, Su R, Liu L. Water resources and climate change. Journal of Water & Climate Change, 2018, 9(2):239-239. https://doi.org/10.2166/wcc.2018.999

[3] Y Picó, D Barceló. Analysis and Prevention of Microplastics Pollution in Water: Current Perspectives and Future Directions. Acs Omega, 2019, 4(4):6709-6719.

[4] Talabi A O, Kayode T J. Groundwater Pollution and Remediation. Journal of Water Resource and Protection, 2019, 11(1):1-19.

[5] Lee E, Ludwig T, Yu B, et al. Neural Network Sampling of the Free Energy Landscape for Nitrogen Dissociation on Ruthenium. Journal of Physical Chemistry Letters, 2021, 12(11):2954-2962.

[6] Kasim N, Nugraha G S. Pengenalan Pola Tulisan Tangan Aksara Arab Menggunakan Metode Convolution Neural Network. Jurnal Teknologi Informasi Komputer dan Aplikasinya (JTIKA ), 2021, 3(1):85-95. https://doi.org/10.29303/jtika.v3i1.136

[7] Gunathilake M B, Senarath T, Rathnayake U. Artificial Neural Network based PERSIANN data sets in evaluation of hydrologic utility of precipitation estimations in a tropical watershed of Sri Lanka. AIMS Geosciences, 2021, 7(3):478–489. https://doi.org/10.3934/geosci.2021027

[8] Deepa D, Singh Y, Wang M C, et al. An automated method for detecting atrial fat using convolutional neural network:. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, 2021, 235(11):1329-1334.

[9] Nuanmeesri S, Chopvitayakun S, Kadmateekarun P, et al. Marigold Flower Disease Prediction through Deep Neural Network with Multimodal Image. International Journal of Engineering Trends and Technology, 2021, 69(7):174-180.

[10] Knysh B, Kulyk Y. Improving a model of object recognition in images based on a convolutional neural network. Eastern-European Journal of Enterprise Technologies, 2021, 3(9(111)):40-50.

[11] Khan A H, Hussain M, Malik M K. Cardiac Disorder Classification by Electrocardiogram Sensing Using Deep Neural Network. Complexity, 2021, 2021(2):1-8. https://doi.org/10.1155/2021/5512243

[12] Wieters K M. Review:Social Capital in Development Planning: Linking the Actors, by Raffaella Y. Nanetti and Catalina Holguin:. Journal of Planning Education and Research, 2021, 41(2):249-251. https://doi.org/10.1177/0739456X19859421

[13] Njagi P N, Midigo R. Alcohol Use among Medical Students: Linking Knowledge as a Social Capital Defining Norms in Learning Institutions. European Journal of Medical and Health Sciences, 2021, 3(1):197-200. https://doi.org/10.24018/ejmed.2021.3.1.504

[14] Jawahar J, Bilal A R, Fatima T, et al. Does organizational cronyism undermine social capital? Testing the mediating role of workplace ostracism and the moderating role of workplace incivility. Career Development International, 2021, 26(5):657-677. https://doi.org/10.1108/CDI-09-2020-0228

[15] Ozanne L K, Ozanne J L. Disaster Recovery: How Ad Hoc Marketing Systems Build and Mobilize Social Capital for Service Delivery:. Journal of Public Policy & Marketing, 2021, 40(3):372-388.

[16] F Martín-Alcázar, M Ruiz-Martínez, G Sánchez-Gardey. The performance of researchers in multidisciplinary research groups: does social capital matter?:. International Review of Administrative Sciences, 2021, 88(2):337-354.

[17] Jankovi D, Novakov M, Petrovi M. Social Capital of Farmers in the Rural Communities of Vojvodina. Contemporary Agriculture, 2021, 70(1-2):20-27.

[18] Jedynak W. The Leader's Role in Building Religious Social Capital: A Religious Regional Community Leader in Poland. Roczniki Nauk Społecznych, 2021, 12(48)(1):33-51. https://doi.org/10.18290/rns20481-2