The Dynamic Model Prediction Study of the Forest Disease, Insect Pest and Rat Based on BP Neural Networks
- Wang Yong
- Wang Gang
- Shengjing Feng
Abstract
This paper introduced BP neural networks, and constructed a dynamic predict model, based on it to predict forest disease and insect and rat pest. Then analyzing and simulating the states in recent ten years with the data produced by the BP neural network model. The result indicates that the BP neural network model is reliable for predicting the forest disease and insect and rat pest.
- Full Text: PDF
- DOI:10.5539/jas.v4n3p291
This work is licensed under a Creative Commons Attribution 4.0 License.
Journal Metrics
- h-index: 67
- i10-index: 839
- WJCI (2022): 1.220
- WJCI Impact Factor: 0.263
Index
- AGRICOLA
- AGRIS
- BASE (Bielefeld Academic Search Engine)
- Berkeley Library
- CAB Abstracts
- CiteFactor
- CiteSeerx
- CNKI Scholar
- Copyright Clearance Center
- CrossRef
- DESY Publication Database
- DTU Library
- EBSCOhost
- Elektronische Zeitschriftenbibliothek (EZB)
- EuroPub Database
- Excellence in Research for Australia (ERA)
- Genamics JournalSeek
- Google Scholar
- Harvard Library
- IDEAS
- Index Copernicus
- Jisc Library Hub Discover
- JournalTOCs
- KindCongress
- LIVIVO (ZB MED)
- LOCKSS
- Max Planck Institutes
- Mendeley
- MIAR
- Mir@bel
- NLM Catalog PubMed
- Norwegian Centre for Research Data (NSD)
- OAJI
- Open J-Gate
- OUCI
- PKP Open Archives Harvester
- Polska Bibliografia Naukowa
- Qualis/CAPES
- RefSeek
- RePEc
- ROAD
- ScienceOpen
- Scilit
- SCiNiTO
- Semantic Scholar
- SHERPA/RoMEO
- Southwest-German Union Catalogue
- Standard Periodical Directory
- Stanford Libraries
- SUDOC
- Technische Informationsbibliothek (TIB)
- Trove
- UCR Library
- Ulrich's
- UniCat
- Universe Digital Library
- WorldCat
- WorldWideScience
- WRLC Catalog
- Zeitschriften Daten Bank (ZDB)
Contact
- Anne BrownEditorial Assistant
- jas@ccsenet.org