Mohammad Diqi
16 Papers
Mohammad Diqi is an academic researcher. The author has contributed to research in topics: Computer science & Mean squared error. The author has an hindex of 1, co-authored 1 publications.
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Papers
StockGAN: robust stock price prediction using GAN algorithm
TL;DR: This study shows how to accurately anticipate stock prices using a prediction model based on the Generative Adversarial Networks (GAN) method, which can be a promising solution for dealing with accurate and dynamic stock prices.
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TwitterGAN: robust spam detection in twitter using novel generative adversarial networks
TL;DR: A novel spam detection model that leverages generative learning techniques is proposed, offering improved performance on vast datasets and changing circumstances, and raising the bar for spam detection research.
8
StockTM: Accurate Stock Price Prediction Model Using LSTM
TL;DR: Wang et al. as discussed by the authors presented a novel stock price prediction model based on the Long Short-Term Memory (LSTM) algorithm, which can obtain good accuracy with a small error rate in an extensive dataset training.
6
Waste Classification using CNN Algorithm
Mohammad Diqi
- 26 Feb 2022
TL;DR: In this paper , the authors used the CNN algorithm to provide a problem-solving strategy to waste classification, which achieved an accuracy of 0.9969 and a loss of 1.0205.
3
Performance evaluation of stock prediction models using emagru
Erizal Erizal,Mohammad Diqi +1 more
TL;DR: This work offers the Exponential Moving Average Gated Recurrent Unit (EMAGRU) model, a model that combines the AntiReLU and ReLU activation functions into the model, and shows low losses and high accuracy.
1