The problem of portfolio optimization has made many advances since Markowitz proposed an average-variance-based optimization. It can be said that the most important achievement of the Markowitz model was the introduction of variance as a risk indicator and indeed, the introduction of a quantitative benchmark into it. This research is a model for predicting value at risk. This model extends the ...

This paper aims to improve the reliability of optimal control using models constructed by machine learning methods. Optimal problems based on such are generally non-convex and difficult solve online. In this paper, we propose a model that combines Hammerstein-Wiener with input convex neural networks, which have recently been proposed in field learning. An important feature is resulting effectiv...

Credit risk management is becoming more and more important in recent years. When a company deals with a financial problem, it may not be able to fulfill its financial obligations, which can cause direct and indirect financial losses to shareholders, creditors, investors and other people in the community. Advanced credit risk models that are based on market value include improving credit quality...

this study aims at comparing the performance of logistic regression, maximum entropy, and multilayer perceptron techniques in preparing the predictive habitat distribution map of amygdalus scoparia in rangelands of qom province. for this purpose, vegetation sampling was done using random systematic methods after identifying pure habitats of this species. for soil sampling, eight profiles were e...

The present sought to draw a comparison between Model Predictive Control performance and two other controllers named Simple PI and Selective PI in controlling large-scale natural gas transport networks. A nonlinear dynamic model of representative gas pipeline was derived from pipeline governing rules and simulated in SIMULINK® environment of MATLAB®. Control schemes were designed to provide a s...

Introduction: Rectal toxicity is a dose limiting issue in prostate cancer radiotherapy. Prediction of these effects may be used to tailor the therapy. The purpose of this work was to develop predictive radiomic models based on clinical, dosimetric and radiomic features extracted from rectal wall magnetic resonance image (MRI).   Materials and Methods: This st...

Application of data mining methods as a decision support system has a great benefit to predict survival of new patients. It also has a great potential for health researchers to investigate the relationship between risk factors and cancer survival. But due to the imbalanced nature of datasets associated with breast cancer survival, the accuracy of survival prognosis models is a challenging issue...

Horizontal directional drilling is usually used in drilling engineering. In a variety of conditions, it is necessary to predict the torque required for performing the drilling operation. Nevertheless, there is presently not a convenient method available to accomplish this task. In order to overcome this difficulty, the current work aims at predicting the required rotational torque (RT) to opera...