The evaluation process necessitates significant work in order to effectively and impartially
assess the growing number of new subjects and interests in courses. This paper aims at …

In recent years, deep learning and its subtopics have found a near gold-rush stature in the
industry. This booming response has not been restricted to niche applications, but rather to …

A generative adversarial network (GAN) is a generative model that is able to generate fresh
content by using several deep learning techniques together. Due to its fascinating …

Analyzing community response has always played an important role in marketing and
development of various products ranging from services to manufacturing. Analyzing the …

Imbalanced datasets often result in poor predictive model performance. To address this,
minority class sample expansion is used, but two challenges remain. The first is to use …

In order to reduce the operational risks of enterprises and help enterprises improve their
core competitiveness, this paper studies the BP neural network prediction method for the …

Artificial Intelligence (AI) technology has quickly developed under the mighty computing
power of computers. At this stage, there are many mature non-destructive testing methods in …

New Approaches in Financial Forecasting on the Symbolic Data Analysis Framework: From
Query and Social Media Data to Text Mining Page 1 New Approaches in Financial Forecasting …

In order to improve the potential returns of stock investors, the analysis of FTS data and the
discovery of changing laws are a major challenge for stock market analysis technology. With …

The Agri-industry forms the backbone of the economy and livelihood. Hence, efficient
planning on resources and ensuring a steady food supply is vital. This model discusses the …