The application research of neural network and BP algorithm in stock price pattern classification and prediction
D Zhang, S Lou - Future Generation Computer Systems, 2021 - Elsevier
Under the background of big data and Internet finance, quantitative investment is becoming
more and more critical, and the prediction of the stock price has become the focus of …
more and more critical, and the prediction of the stock price has become the focus of …
Agricultural product price forecasting methods: research advances and trend
L Wang, J Feng, X Sui, X Chu, W Mu - British Food Journal, 2020 - emerald.com
Purpose The purpose of this paper is to provide reference for researchers by reviewing the
research advances and trend of agricultural product price forecasting methods in recent …
research advances and trend of agricultural product price forecasting methods in recent …
Particle swarm optimization performance improvement using deep learning techniques
Deep learning is widely used to automate processes, improve performance, detect patterns,
and solve problems. Thus, applications of deep learning are limitless. Particle swarm …
and solve problems. Thus, applications of deep learning are limitless. Particle swarm …
An improved hybrid grey wolf optimization algorithm
Z Teng, J Lv, L Guo - Soft computing, 2019 - Springer
The existing grey wolf optimization algorithm has some disadvantages, such as slow
convergence speed, low precision and so on. So this paper proposes a grey wolf …
convergence speed, low precision and so on. So this paper proposes a grey wolf …
Deep Learning Techniques for Peer-to-Peer Physical Systems Based on Communication Networks
P Ajay, B Nagaraj, R Huang - Journal of Control Science and …, 2022 - search.proquest.com
Existing communication networks have inherent limitations in translation theory and adapt to
address the complexity of repairing new remote applications at the highest possible level …
address the complexity of repairing new remote applications at the highest possible level …
Improving extreme learning machine by competitive swarm optimization and its application for medical diagnosis problems
Abstract Extreme Learning Machine (ELM) is swiftly gaining popularity as a way to train
Single hidden Layer Feedforward Networks (SLFN) for its attractive properties. ELM is a fast …
Single hidden Layer Feedforward Networks (SLFN) for its attractive properties. ELM is a fast …
A BP-PID controller-based multi-model control system for lateral stability of distributed drive electric vehicle
The lateral stability is the crucial feature in a distributed drive electronic vehicle (DDEV). A
high speed DDEV in a sharp turn may lose the lateral stability when it encounters fast varied …
high speed DDEV in a sharp turn may lose the lateral stability when it encounters fast varied …
Synergy evaluation model of container multimodal transport based on BP neural network
W Zhu, H Wang, X Zhang - Neural Computing and Applications, 2021 - Springer
With the rapid development of economic globalization, the trade of various countries has
become increasingly close and thus the rapid growth of container transportation business …
become increasingly close and thus the rapid growth of container transportation business …
A BP neural network prediction model based on dynamic cuckoo search optimization algorithm for industrial equipment fault prediction
The fault prediction problem for modern industrial equipment is a hot topic in current
research. So, this paper first proposes a dynamic cuckoo search algorithm. The algorithm …
research. So, this paper first proposes a dynamic cuckoo search algorithm. The algorithm …
Plant miRNA–lncRNA interaction prediction with the ensemble of CNN and IndRNN
P Zhang, J Meng, Y Luan, C Liu - … Sciences: Computational Life Sciences, 2020 - Springer
Non-coding RNA (ncRNA) plays an important role in regulating biological activities of
animals and plants, and the representative ones are microRNA (miRNA) and long non …
animals and plants, and the representative ones are microRNA (miRNA) and long non …