... ( PRISMA ) 2020 protocol to select 135 peer-reviewed articles published between 1968 and 2025, complemented by an ad hoc search to ensure comprehensiveness. The analysis encompassed both traditional statistical forecasting models and contemporary machine learning ( ML ) and deep learning ( DL...

... (b), lip length (S), the bearing length (i), number of holes (n) and radius of the hole to the beam height (r/h). Subsequently, machine learning ( ML ) techniques are applied to train five ML algorithms using the extensive dataset generated by the conducted...

...Md Rabiul Hasan; Aojoy Kumar Shuvo; Ehsanul Bashar Pranto; Mehedi Hasan; Md Mintu Miah Purpose The purpose of this study is to predict the compressive strength of hybrid-fiber-reinforced recycled aggregate concrete ( HFRRAC ) using machine learning ( ML ) models. The aim is to address...

... process integrates a two-step machine learning framework. First, the K-Prototypes algorithm is applied to cluster blocks based on geological and spatial characteristics. Subsequently, a multilayer perceptron ANN refines the classification by smoothing categorical boundaries, ensuring spatial coherence...

...Mehdi Ranjbar-Roeintan; Sajad Ahmadian; Ali Soleymani Purpose The study aims to predict a low-velocity impact on a plate reinforced with carbon nanotubes (CNTs) using machine learning models. Design/methodology/approach The first-order shear deformation plate theory (FSDT) is used to express...

... This research uses machine learning (ML) techniques to predict soil slope failure. Due to the lack of analytical solutions for measuring FS and PF, it is more convenient to use surrogate models like probabilistic modeling, which is suitable for performing repetitive calculations to compute the effect...

... and the battery; and measurements of humidity, pressure and radiation values in the panel’s environment. These data were monitored and recorded in real-time through a computer interface and mobile interface enabling remote access. For prediction purposes, machine learning methods, including the gradient boosting...

... model is proposed that uses the co-Kriging method for dimension reduction of a 3D model to a 2D model. In Bo Zhang et al. (2006) , a method based on the boundary element method and charge simulation method has been used to model the insulators and Corona ring. Also, recently, machine learning...

... sensors as well as a variety of other sources. It is difficult to capture and process large amounts of sensor data in real time. Sensor data is consumed by streaming analytics platforms that use big data technologies, which is then processed using a range of deep learning and machine learning techniques...

...Catherene Julie Aarthy C.; Rajkumar N.; V.P. Sriram; Badrinarayanan M.K.; K. Bhavana Raj; Rajan Patel Purpose The purpose of this paper used for catastrophe and pandemic preparedness was the craft of machine learning calculations. ML is the latest globe learning technique to assist...

...Hishan S. Sanil; Deepmala Singh; K. Bhavana Raj; Somya Choubey; Narinder Kumar Kumar Bhasin; Ranjeeta Yadav; Kamal Gulati Purpose “Machine learning (ML)” in business aids in increasing company scalability and boosting company operations for businesses all over the world. “Artificial intelligence...

... method increasingly being used in many speech processing applications. The paper aims to use Compressive sensing algorithm for hearing aid applications to reduce surrounding noise. Design/methodology/approach In this work, the authors propose a machine learning algorithm for improving the performance...

... requirements. Not only the data is getting increased but also the attacks are increasing very rapidly. Deep learning and machine learning techniques are very trending in the area of research in the area of network security. A lot of work has been done in this area by still evolutionary algorithms along...

... are discussed as follows: Mohammad Shabaz can be contacted at: bhatsab4@gmail.com 24 02 2021 25 03 2021 26 03 2021 © Emerald Publishing Limited 2021 Emerald Publishing Limited Licensed re-use rights only Sentiment analysis Sarcasm Machine learning In this era...

... of affected persons is urgently in demand. Diagnostic methods applied in hospitals are time-consuming, which delay the identification of positive patients. This study aims to develop machine learning-based diagnosis model which can predict positive cases and helps in decision-making. Design/methodology...

... and prediction of survival before the targeted intervention and diagnosis, in particular the triage of the vast COVID-19 explosive epidemic. Design/methodology/approach Automated machine learning (ML) provides resources and platforms to render ML available to non-ML experts, to boost efficiency in ML...

... discriminative descriptors from diseased gene sequences based on splicing variants and to provide an effective machine learning solution for predicting the type of muscular dystrophy disease with the splicing mutations. Multi-class classification is worked out through data modeling of gene sequences...