Predicting compressive strength of cement-stabilized earth blocks using machine learning models incorporating cement content, ultrasonic pulse velocity, and …
N Sathiparan, P Jeyananthan - Nondestructive Testing and …, 2024 - Taylor & Francis
The quality monitoring technique for Cement stabilised earth blocks (CSEBs) is so
challenging that it is often neglected. This study has investigated the possibility of using …
challenging that it is often neglected. This study has investigated the possibility of using …
Estimation of static Young's modulus of sandstone types: effective machine learning and statistical models
N Liu, Y Sun, J Wang, Z Wang, A Rastegarnia… - Earth Science …, 2024 - Springer
The elastic modulus is one of the important parameters for analyzing the stability of
engineering projects, especially dam sites. In the current study, the effect of physical …
engineering projects, especially dam sites. In the current study, the effect of physical …
Twin Transformer using Gated Dynamic Learnable Attention mechanism for Fault Detection and Diagnosis in the Tennessee Eastman Process
MA Labbaf-Khaniki, M Manthouri - arXiv preprint arXiv:2403.10842, 2024 - arxiv.org
Fault detection and diagnosis (FDD) is a crucial task for ensuring the safety and efficiency of
industrial processes. We propose a novel FDD methodology for the Tennessee Eastman …
industrial processes. We propose a novel FDD methodology for the Tennessee Eastman …
Enhancing Price Prediction in Cryptocurrency Using Transformer Neural Network and Technical Indicators
MAL Khaniki, M Manthouri - arXiv preprint arXiv:2403.03606, 2024 - arxiv.org
This study presents an innovative approach for predicting cryptocurrency time series,
specifically focusing on Bitcoin, Ethereum, and Litecoin. The methodology integrates the use …
specifically focusing on Bitcoin, Ethereum, and Litecoin. The methodology integrates the use …
[HTML][HTML] Developing some models to predict the uniaxial compressive strength of various sedimentary rocks (Case studies: Large dam site and mine in Southeast …
Z Wang, Z Zhou, T Sun, J Wang, N Liu… - Case Studies in …, 2024 - Elsevier
Direct determination of uniaxial compressive strength (UCS) is time-consuming, expensive,
and challenging. Therefore, this study aims to indirectly predict UCS using statistical and …
and challenging. Therefore, this study aims to indirectly predict UCS using statistical and …
A Novel Approach to Chest X-ray Lung Segmentation Using U-net and Modified Convolutional Block Attention Module
MAL Khaniki, M Manthouri - arXiv preprint arXiv:2404.14322, 2024 - arxiv.org
Lung segmentation in chest X-ray images is of paramount importance as it plays a crucial
role in the diagnosis and treatment of various lung diseases. This paper presents a novel …
role in the diagnosis and treatment of various lung diseases. This paper presents a novel …
Comprehensive study on the Python-based regression machine learning models for prediction of uniaxial compressive strength using multiple parameters in …
S Kochukrishnan, P Krishnamurthy, N Kaliappan - Scientific Reports, 2024 - nature.com
The strength of rock under uniaxial compression, commonly known as Uniaxial
Compressive Strength (UCS), plays a crucial role in various geomechanical applications …
Compressive Strength (UCS), plays a crucial role in various geomechanical applications …
Adaptive PID controller using deep deterministic policy gradient for a 6D hyperchaotic system
MA Labbaf Khaniki, A Samii… - Transactions of the …, 2024 - journals.sagepub.com
This article introduces a method for the adaptive control of a six-dimensional (6D)
hyperchaotic system using a multi-input multi-output (MIMO) approach, leveraging the deep …
hyperchaotic system using a multi-input multi-output (MIMO) approach, leveraging the deep …
Whale Optimization Algorithm-based Fractional Order Fuzzy Type-II PI Control for Modular Multilevel Converters
MA Labbaf-Khaniki, M Manthouri… - arXiv preprint arXiv …, 2024 - arxiv.org
Designing a robust controller for Modular Multilevel Converters (MMCs) is crucial to ensure
stability and optimal dynamic performance under various operating conditions, including …
stability and optimal dynamic performance under various operating conditions, including …
Development of a New Modified Sonar Inspired Optimization based on Machine Learning Methods for Evaluating Compressive of High-Performance Concrete
A Nikkhoo, A Moshtagh… - Journal of Rehabilitation …, 2024 - civiljournal.semnan.ac.ir
The nonlinearity observed in high-performance concrete (HPC) can be attributed to its
distinctive features. This study examines the effectiveness of expert frameworks in …
distinctive features. This study examines the effectiveness of expert frameworks in …