In the present study, two different data-driven models, artificial neural network (ANN) and multiple linear regression (MLR) models, have been developed to predict the 28 days compressive strength of concrete. Seven different parameters namely 3/4 mm sand, 3/8 mm sand, cement content, gravel, maximums size of aggregate, fineness modulus, and water-cement ratio were considered as input variables...

We perform regression modeling to obtain estimates of the number of cycles (used as a proxy for application performance). A linear regression is performed in which the response (number of cycles) is a weighted sum of predictor variables (such as L1P misses, AXU instructions, XU instructions, FP operations, etc.) plus some random noise. Since linear relationships may not always be adequate to mo...

The machine learning program GOLEM from the field of inductive logic programming was applied to the drug design problem of modeling structure-activity relationships. The training data for the program were 44 trimethoprim analogues and their observed inhibition of Escherichia coli dihydrofolate reductase. A further 11 compounds were used as unseen test data. GOLEM obtained rules that were statis...

This work aims to develop statistical models for ultrafine/fine particle number emission rates from a diesel bus, to evaluate the explanatory power of engine operating variables. Emissions were recorded by using on-board instrumentation in two types of real-world driving conditions: a freeway commuting route and a within-city-limits bus route, with stop and go due to intersections and bus stops...

Objectives: The consumption of electricity and its costs are expected to be increased in Saudi Arabia due to its rapid growth in population. As the Kingdom is characterized by extreme hot climate, a massive amount of electricity consumed by the residential sector goes to power air conditioners. To control this huge amount of energyconsumedin homes, thermal models have been generated with two or...

This study aims to evaluate the impact of pavement physical characteristics on the frequency of single-vehicle run-off-road (ROR) crashes in two-lane separated rural highways. In order to achieve this goal and to introduce the most accurate crash prediction model (CPM), authors have tried to develop generalized linear models, including the Poisson regression (PR), negative binomial regression (...