Multi-criterion decision making (MCDM) methods can derive alternative rankings as
solutions to decision-making problems based on survey or historical data about the …

An accurate estimation of forests' aboveground biomass (AGB) is required because of its
relevance to the carbon cycle, and because of its economic and ecological importance. The …

Support Vector Machine (SVM) algorithm is a machine learning algorithm that is used to
classify data by finding the best hyperplane that separates classes. In the SVM algorithm …

Machine learning methods have been successfully applied to many engineering disciplines.
Prediction of the concrete compressive strength (fc) and slump (S) is important in terms of …

This paper seeks to use artificial intelligence blockchain algorithms to ensure safe
verification of medical institution PHR data and accurate verification of medical data as …

High-temperature alloy design requires a concurrent consideration of multiple mechanisms
at different length scales. We propose a workflow that couples highly relevant physics into …

Leaf area index (LAI) is a crucial crop biophysical parameter that has been widely used in a
variety of fields. Five state-of-the-art machine learning regression algorithms (MLRAs) …

Applying the optimum rate of fertilizer nitrogen (N) is a critical factor for field management.
Multispectral information collected by active canopy sensors can potentially indicate the leaf …

Minimum miscibility pressure (MMP) is a key parameter in the successful design of miscible
gases injection such as CO 2 flooding for enhanced oil recovery process (EOR). MMP is …

A holistic occupational and economy-wide framework for salary prediction is developed and
tested using statistical machine learning (ML). Predictive models are developed based on …