Constitutive modeling of clay is an important research in geotechnical engineering. It is difficult to use precise mathematical expressions to approximate stress-strain relationship of clay. Artificial neural network (ANN) and support vector machine (SVM) have been successfully used in constitutive modeling of clay. However, generalization ability of ANN has some limitations, and application of...

according to recent developments of predicting methodsin financial markets, and since the stock price is one of the mostimportant factors for investment decision-making, and its predictioncan play an important role in this field, the aim of this study is toprovide a model to predict the stock price movement with highaccuracy. accordingly, a hybrid model for predicting the stock pricemovement us...

When the disaster occurs, the social network site such as Twitter is increasingly being used for helping direct rescue operations. This article describes the methods we used in the Fire2017. We regarded the distinction of need-tweets and availability-tweets as classification tasks, and the logistic regression and Support Vector Machine are used to decide the type of the tweets. In the need and ...

Semi supervised learning methods have gained importance in today’s world because of large expenses and time involved in labeling the unlabeled data by human experts. The proposed hybrid approach uses SVM and Label Propagation to label the unlabeled data. In the process, at each step SVM is trained to minimize the error and thus improve the prediction quality. Experiments are conducted by using ...

We propose a novel idea of regression – balancing the distances from a regression function to all examples. We created a method, called balanced support vector regression (balanced SVR) in which we incorporated this idea to support vector regression (SVR) by adding an equality constraint to the SVR optimization problem. We implemented our method for two versions of SVR: ε-insensitive support ve...

Algorithmic decision making systems are ubiquitous across a wide variety of online as well as offline services. These systems rely on complex learning methods and vast amounts of data to optimize the service functionality, satisfaction of the end user and profitability. However, there is a growing concern that these automated decisions can lead, even in the absence of intent, to a lack of fairn...