The prediction of shear resistance in reinforced concrete (RC) beams, which are strengthened using externally bonded reinforcements (EBR), poses a significant challenge due to the complex nature of shear-resisting mec...
详细信息
The prediction of shear resistance in reinforced concrete (RC) beams, which are strengthened using externally bonded reinforcements (EBR), poses a significant challenge due to the complex nature of shear-resisting mechanisms and their complex interaction. Conventional models have been shown to have limited reliability and produce weak predictions. However, recent advancements in machinelearning techniques and artificial intelligence have led to the development of several models in various studies that aim to predict the contribution of EBR-FRP to the shear resistance of RC beams. This study makes an attempt to enhance the predictive performance of the models by considering various factors. First, a comprehensive review is conducted on previous ML models, with a discussion on their strengths and weaknesses. The limitations of these models are addressed. Furthermore, potential approaches to improve the model predictive performance are discussed, and a new model is proposed.
This paper proposes a system that integrates real-time Speech Emotion Recognition (SER) into live calls, allowing event organizers to dynamically personalize content based on participants' emotional *** machine le...
详细信息
Early detection of Alzheimer's disease (AD) is crucial for timely intervention and slowing its progression. This research leverages neuroimaging-based machinelearning to classify cognitive impairment levels using...
详细信息
This research paper proposes a curriculum for a five-year academic program with a bachelor's degree (honors) in intelligent systemsengineering and software engineering and a master's degree in intelligent sys...
详细信息
ISBN:
(纸本)9798350361513;9798350372304
This research paper proposes a curriculum for a five-year academic program with a bachelor's degree (honors) in intelligent systemsengineering and software engineering and a master's degree in intelligent systemsengineering and software engineering. This program includes courses in data structures, compiler design, operating system design, firmware design, database systems, computer graphics and virtual reality design, static and dynamic website design, development of chatbots and voice assistants, software engineering methodology, knowledge-based systems, fuzzy logic, neural networks, evolutionary computation, evolutionary multiojective optimization, machinelearning, image processing, computer vision, pattern recognition, voice recognition, natural language processing, data science, control systems, intelligent control systems, robotics, digital signal processing, mathematics, engineering physics, biology, etc. These degrees will allow graduates to have a good understanding of all of the main branches of intelligent systemsengineering and software engineering as well as other relevant subjects in electrical and computer engineering.
In the largely expanding landscape of cloud service providers, the selection of an optimal cloud platform has emerged as a critical consideration. It would offer potential cost saving and operational efficiency enhanc...
详细信息
This paper proposes a classification prediction model of metabolic fatty liver based on PMAULD-TabNet, which can help doctors realize early screening for people prone to fatty liver disease, help patients realize risk...
详细信息
ISBN:
(纸本)9798350351040;9798350351033
This paper proposes a classification prediction model of metabolic fatty liver based on PMAULD-TabNet, which can help doctors realize early screening for people prone to fatty liver disease, help patients realize risk assessment and implement correct and effective treatment as soon as *** physical examination data of 2568 patients in the outpatient department of Infection, Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine were selected as the research objects, and the relevant data cohort was *** order to improve the accuracy of the model, decision tree, support vector machine, Bagging, random forest, XGBoost and PMAFLD-TahNet machinelearning algorithms were used to construct the classification prediction models of fatty liver disease, respectively, and to predict the classification of fatty liver disease in 2568 cases of physical examination *** the experimental results, the area under ROC curve of the fatty liver prediction model established by PMAFI,D-TabNet algorithm was 0.7, the accuracy rate was 0.801, and the accuracy rate was 0.872, which were higher than other machinelearning *** can be seen that the model containing PMAULD-TabNet framework has better predictive classification performance.
The merger of artificial intelligence (AI) and machinelearning (ML) technologies has drastically changed the field of fraud detection in digital banking in recent years. The increasing frequency of digital transactio...
详细信息
This study assesses advanced machinelearning algorithms, namely XGboost and Gradient Boosting machine (GBM), for fraud detection in social media profiles and payment systems. It focuses on two very different types of...
详细信息
Blockchain technology offers transformative potential for enhancing the security of online banking systems from the intruders. This paper investigates the application of blockchain in secure banking, focusing on the i...
详细信息
Electromyography study focuses on the classification of electromyography (EMG) signals using machinelearning (ML) techniques. The classification of EMG signals with ML techniques improves the response and accuracy of...
详细信息
暂无评论