Bayesian methods are a powerful tool in many areas of science and engineering, especially
statistical physics, medical sciences, electrical engineering, and information sciences. They …

In this work, we present a survey on different topics related to Internal Combustion (IC)
engines. The purpose of this work is to show the evolution on modeling, use of biofuels …

Due to the increasing use of automobiles, the transportation industry is facing challenges of
increased emissions, driver safety concerns, travel demand, etc. Hence, automotive …

Ternary-blend concrete is a complex composite material, and the nonlinearity in its
compressive strength behavior is unquestionable. Entirely many models have been …

There is a substantial interest in retrieving images from a large database using the textual
information contained in the images. An algorithm which will automatically locate the textual …

Abstract Homogeneous Charge Compression Ignition (HCCI) engine is a prospective
technology that effectively utilizes net carbon-neutral biofuels to achieve ultra-low nitrogen …

In this study, a model is proposed by applying the least squares support vector machine
(LSSVM). In addition, genetic algorithm is used for selection and optimization of …

Modern machine learning algorithms excel in a great variety of tasks, but at the same time, it
is also known that those complex models need to deal with uncertainty from different …

Various parameters affect thermal conductivity of nanofluid; however, some of them are
more influential such as temperature, size and type of nano particles and volumetric …

This study presents the optimization of biodiesel engine performance that can achieve the
goal of fewer emissions, low fuel cost and wide engine operating range. A new biodiesel …