نتایج جستجو برای: machine models
تعداد نتایج: 1124872 فیلتر نتایج به سال:
Abstract Under what conditions does machine learning (ML) model opacity inhibit the possibility of explaining and understanding phenomena? In this article, I argue that nonepistemic values give shape to ML problem even if we keep researcher interests fixed. Treating models as an instance doing model-based science explain understand phenomena reveals there is (i) external problem, where presence...
Much research has introduced linear or nonlinear models using statistical models and machine learning tools in artificial intelligence to estimate Iran's rate of return. The primary purpose of these methods is simultaneously use different independent variables to improve stock return rates' modeling. However, in predicting the rate of return, in addition to the modeling method, the degree of co...
In this paper, we consider the problem of scheduling on two-machine permutation flowshop with minimal time lags between consecutive operations of each job. The aim is to find a feasible schedule that minimizes the total tardiness. This problem is known to be NP-hard in the strong sense. We propose two mixed-integer linear programming (MILP) models and two types of valid inequalities which aim t...
The aim of this study is to predict and model flood hazard in the city of Nowshahr, Mazandaran province using machine learning models. The criteria and indicators affecting flood hazard were identified based on the review of resources, and then the indicators were converted into rasters in ArcGIS environment, and finally standardized by fuzzy method for use in the models. K-nearest neighbor ...
In real world scheduling applications, machines might not be available during certain time periods due to deterministic or stochastic causes. In this article, the machine scheduling with availability constraints for both deterministic and stochastic cases with different environments, constraints and performance measures will be discussed. The existing body of research work in the literature wil...
This work uses sequence-to-sequence (seq2seq) models pre-trained on monolingual corpora for machine translation. We pre-train two seq2seq with the source and target languages, then combine encoder of language model decoder model, i.e., cross-connection. add an intermediate layer between to help mapping each other since modules are completely independently. These can as a multilingual because on...
A comparative workflow, including linear and non-linear QSAR models, was carried out to evaluate the predictive accuracy of models and predict the inhibition activity of a series of aryl-substituted isobenzofuran-1(3H)-ones. The data set consisted of 34 compounds was classified into the training and test sets, randomly. Molecular descriptors were selected using the genetic algorithm (GA) as a f...
permeability prediction problem has been examined using several methods such as empirical formulas, regression analysis and intelligent systems especially neural networks and fuzzy logic. this study proposes an improved and novel model for predicting permeability from conventional well log data. the methodology is integration of empirical formulas, multiple regression and neuro-fuzzy in a commi...
نمودار تعداد نتایج جستجو در هر سال
با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید