Hybrid Functional Link Neural Networks for Soybean Price Forecast

DOI

10.2991/978-94-6463-136-4_48How to use a DOI?

Keywords

Functional Link Neural Networks; Whale Optimization Algorithm; Particle Swarm Optimisation Algorithm; Harris Hawks Optimization Algorithm

Abstract

Drastic change in crop prices is observed due to climatic changes, natural calamities and lack of quantity of a specific commodity. Crop price prediction plays key role in effective farm management. Farmers are not able to predict these crop prices and facing massive loss. These aspects pressure us to use advanced technology and develop accurate, reliable and efficient crop price prediction system. Crop price prediction also helps agriculture based industries and policy-makers. There are many price-sensitive crops like tomatoes, onions, potatoes, Soybean and other food grains, which need prior price prediction so that farmers can take wise decisions on which crop to cultivate. Functional link neural net- work is chosen to develop Basic network for Soybeans price prediction. Optimization algorithms like whale optimization, particle swarm optimization and Harris Hawks Optimization are used to calculate appropriate biases and weights. Dataset is taken from daily reports issued by Chicago Mercantile Exchange (CME).Most efficient hybrid FLNN with associated Expansion function, activation function and learning scheme for predicting crop price could be found out through our study.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - S. Dhanalakshmi
AU  - S. Rajakumar
AU  - A. S. Anakath
AU  - R. Kannadasan
AU  - S. Ambika
PY  - 2023
DA  - 2023/05/01
TI  - Hybrid Functional Link Neural Networks for Soybean Price Forecast
BT  - Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
PB  - Atlantis Press
SP  - 569
EP  - 581
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-136-4_48
DO  - 10.2991/978-94-6463-136-4_48
ID  - Dhanalakshmi2023
ER  -