[HTML][HTML] Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges
The growth of the construction industry is severely limited by the myriad complex challenges
it faces such as cost and time overruns, health and safety, productivity and labour shortages …
it faces such as cost and time overruns, health and safety, productivity and labour shortages …
Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing
This article surveys and organizes research works in a new paradigm in natural language
processing, which we dub “prompt-based learning.” Unlike traditional supervised learning …
processing, which we dub “prompt-based learning.” Unlike traditional supervised learning …
How can artificial intelligence impact sustainability: A systematic literature review
We need a proper mechanism to manage issues related to our environment, economy, and
society to proceed toward sustainability. Many researchers have worked for sustainable …
society to proceed toward sustainability. Many researchers have worked for sustainable …
Artificial intelligence for the metaverse: A survey
Along with the massive growth of the Internet from the 1990s until now, various innovative
technologies have been created to bring users breathtaking experiences with more virtual …
technologies have been created to bring users breathtaking experiences with more virtual …
A systematic review and meta-analysis of machine learning, deep learning, and ensemble learning approaches in predicting EV charging behavior
Abstract Machine learning (ML) and deep learning (DL) have enabled algorithms to
autonomously acquire knowledge from data, facilitating predictive and decision-making …
autonomously acquire knowledge from data, facilitating predictive and decision-making …
Classification based on decision tree algorithm for machine learning
B Charbuty, A Abdulazeez - Journal of Applied Science and Technology …, 2021 - jastt.org
Decision tree classifiers are regarded to be a standout of the most well-known methods to
data classification representation of classifiers. Different researchers from various fields and …
data classification representation of classifiers. Different researchers from various fields and …
Categorical depth distribution network for monocular 3d object detection
Monocular 3D object detection is a key problem for autonomous vehicles, as it provides a
solution with simple configuration compared to typical multi-sensor systems. The main …
solution with simple configuration compared to typical multi-sensor systems. The main …
Mechanical behavior of high-entropy alloys
Research in the field of high-entropy alloys has been surging since the 2010s. As widely
acknowledged, research interests in this field are largely sparked by the enormous …
acknowledged, research interests in this field are largely sparked by the enormous …
Heart disease prediction using supervised machine learning algorithms: Performance analysis and comparison
Abstract Machine learning and data mining-based approaches to prediction and detection of
heart disease would be of great clinical utility, but are highly challenging to develop. In most …
heart disease would be of great clinical utility, but are highly challenging to develop. In most …
CatBoost for big data: an interdisciplinary review
Abstract Gradient Boosted Decision Trees (GBDT's) are a powerful tool for classification and
regression tasks in Big Data. Researchers should be familiar with the strengths and …
regression tasks in Big Data. Researchers should be familiar with the strengths and …