Ali Hasan Dakheel^1,*, Mohammed Raheem Mohammed¹, Zainab Ali Abd Alhuseen¹, Wassan Adnan Hashim^2,3

Intelligent Automation & Soft Computing, Vol.40, pp. 195-220, 2025, DOI:10.32604/iasc.2025.061622 - 28 February 2025

Abstract The prediction of pregnancy-related hazards must be accurate and timely to safeguard mother and fetal health. This study aims to enhance risk prediction in pregnancy with a novel deep learning model based on a Long Short-Term Memory (LSTM) generator, designed to capture temporal relationships in cardiotocography (CTG) data. This methodology integrates CTG signals with demographic characteristics and utilizes preprocessing techniques such as noise reduction, normalization, and segmentation to create high-quality input for the model. It uses convolutional layers to extract spatial information, followed by LSTM layers to model sequences for superior predictive performance. The overall More >

Jiachen Li^1,2, Wenlong Deng³, Shan Qing^1,2,*, Yiqin Liu⁴, Hao Zhang^1,2, Min Zheng^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.8, pp. 2181-2200, 2023, DOI:10.32604/fdmp.2023.027299 - 04 April 2023

Abstract In this study, comparing multiple models of machine learning, a multiple linear regression (MLP), multilayer feed-forward artificial neural network (BP) model, and a radial-basis feed-forward artificial neural network (RBF-BP) model are selected for the optimization of the thermal properties of TiO₂/water nanofluids. In particular, the least squares support vector machine (LS-SVM) method and radial basis support vector machine (RB-SVM) method are implemented. First, curve fitting is performed by means of multiple linear regression in order to obtain bivariate correlation functions for thermal conductivity and viscosity of the nanofluid. Then the aforementioned models are used for a More >

Ushaa Eswaran^1,*, S. Anand²

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1917-1928, 2023, DOI:10.32604/csse.2023.032523 - 09 February 2023

Abstract Colon cancer is the third most commonly diagnosed cancer in the world. Most colon AdenoCArcinoma (ACA) arises from pre-existing benign polyps in the mucosa of the bowel. Thus, detecting benign at the earliest helps reduce the mortality rate. In this work, a Predictive Modeling System (PMS) is developed for the classification of colon cancer using the Horizontal Voting Ensemble (HVE) method. Identifying different patterns in microscopic images is essential to an effective classification system. A twelve-layer deep learning architecture has been developed to extract these patterns. The developed HVE algorithm can increase the system’s performance… More >

Oakyoung Han¹, Jaehyoun Kim^2,*

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2621-2632, 2021, DOI:10.32604/cmc.2021.014665 - 13 April 2021

Abstract The analysis of large time-series datasets has profoundly enhanced our ability to make accurate predictions in many fields. However, unpredictable phenomena, such as extreme weather events or the novel coronavirus 2019 (COVID-19) outbreak, can greatly limit the ability of time-series analyses to establish reliable patterns. The present work addresses this issue by applying uncertainty analysis using a probability distribution function, and applies the proposed scheme within a preliminary study involving the prediction of power consumption for a single hotel in Seoul, South Korea based on an analysis of 53,567 data items collected by the Korea… More >