Stock market price data is generated in huge volume and it changes every second. Stock market is a complex and challenging system where people will either gain money or lose their entire life savings. In this work, an attempt is made for prediction of stock market trend. Two models are ...
This paper presents a scheme using Differential Evolution based Functional Link Artificial Neural Network(FLANN) to predict the Indian Stock Market Indices. The Model uses Back-Propagation (BP) algorithm and Differential Evolution (DE) algorithm respectively for predicting the Stock Price Indices or one...
Since the development of machine learning, predicting stock market trends has become a captivating task, impacted by economic data, politics, and investor mood. The complexity of these components makes reliable prediction challenging. In this work, we analyze multiple models, including statistics, linea...
Integrating Navier-Stokes equation and neoteric iForest-BorutaShap-Facebook's prophet framework for stock market prediction: An application in Indian context 2022, Expert Systems with Applications Show abstract Stock Market Analysis Using Time Series Relational Models for Stock Price Prediction ...
In stock market forecasting, the identification of critical features that affect the performance of machine learning (ML) models is crucial to achieve accurate stock price predictions. Several review papers in the literature have focused on various ML, s
support vector machines, hidden Markov models and nearest-neighbour methods were trained on the forecasted regional avalanche danger (European avalanche danger ... M Schirmer,M Lehning,J Schweizer - 《Journal of Glaciology》 被引量: 47发表: 2009年 On-line Handwriting Recognition of Indian Scripts ...
UrbanGPT: Spatio-Temporal Large Language Models. Zhonghang Li (South China University of Technology & The University of Hong Kong, Guangzhou), Lianghao Xia, Jiabin Tang, Yong Xu, Lei Shi, Long Xia, Dawei Yin, Chao Huang. KDD 2024 [link] An Open and Large-Scale Dataset for Multi-Modal Cl...
From Text Representation to Financial Market Prediction: A Literature Review 2022, Information (Switzerland) Classification of m-payment users’ behavior using machine learning models 2022, Journal of Financial Services Marketing S_I_LSTM: stock price prediction based on multiple data sources and sentimen...
They state the properties of ML-models to be capable of coping with non-stationary or nonlinear data, among others [31]. Maqbool et al. [36] proposes solid results in the context of sentiment analysis applied for stock series predictions by applying DL-MLP regressors. Further, Übeyli [37...
UrbanGPT: Spatio-Temporal Large Language Models. Zhonghang Li (South China University of Technology & The University of Hong Kong, Guangzhou), Lianghao Xia, Jiabin Tang, Yong Xu, Lei Shi, Long Xia, Dawei Yin, Chao Huang. KDD 2024 [link] An Open and Large-Scale Dataset for Multi-Modal Cl...