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Estimating unstable systems typically requires additional system identification techniques. In this paper, we consider the weighted null-space fitting method, a three step method that is asymptotically efficient for stable systems. This method first estimates a high order ARX model and then reduces it to a structured model with lower variance using weighted least squares. However, with unstable systems,...
Nearly 1.3 million people die each year in traffic-related accidents, whereas an additional 20–50 million people are injured. Introducing autonomous vehicles would aim to reduce these numbers by removing the driver from the loop entirely and thus removing the human error. Intersections are considered a complex traffic situation for autonomous vehicles. Functions which could accurately foresee future...
Software effort estimation influences almost all the process of software development such as: bidding, planning, and budgeting. Hence, delivering an accurate estimation in early stages of the software life cycle may be the key of success of any project. To this aim, many solo techniques have been proposed to predict the effort required to develop a software system. Nevertheless, none of them proved...
Weighted prediction (WP) is an efficient tool for encoding of video with brightness variations, if WP parameters can be estimated accurately. In this paper, an improved estimation method for WP parameters of advanced video coding system (AVS) is proposed. To find a best matching block in reference for current block to be encoded, a motion search scheme is presented. Each block in a searching window...
In response to globalization, International Financial Reporting Standards (IFRS) has become the norm of the global capital markets. Companies preparing financial statements using IFRS may make the financial situation fully disclosed. Nevertheless, an overestimated accrual expense of a balance sheet may not only underestimate the earnings data, but also increase the cash outflows of the statement of...
Electricity is one of the most important needs of human life. In order to provide this need sufficiently, demand for the electricity needs to be predicted in advance. Conducting production oriented studies based on the estimation results is a must. In this study, electricity consumption data of Turkey between the years 1970 and 2014 were collected from Turkish Statistical Institute. Using these data,...
Weather forecast is a valuable practical problem and has important implications for agriculture, industry and other services. There have been different proposed methods to forecast the weather parameters [3, 6, 8, 9], but the parameters of the prediction model depends on the geographical conditions and the economic development of the given area. Therefore, for every new location, we need to redefine...
Online social media networks play important roles for people to share opinions, communicate with others. One of important features behind these activities is trust. This paper investigates the trust model in Online social media networks. Considering the interaction between two users and the reputation in the social networks, this trust model gives a definition about the trust value between two users...
Traffic engineering (TE) plays an essential role in deciding routes that effectively use network resources. The TE controller should handle the uncertainty due to the lags and lacks of collected network information. Many previous work partially tackled this uncertainty problem in various aspects e.g. data collection, estimation, prediction, routing with uncertain traffic. However there are few studies...
In order to reduce the curtailment of renewable generation in periods of low load, operators can limit the import net transfer capacity (NTC) of interconnections. This paper presents a probabilistic approach to support the operator in setting the maximum import NTC value in a way that the risk of curtailment remains below a pre-specified threshold. Main inputs are the probabilistic forecasts of wind...
Recently hospitals struggle to control the cost of care while maintaining optimal outcomes. To respond to this challenge, we developed an interactive web platform which utilizes a multiple linear regression model. The user can create and furthermore alter a clinical scenario, during a patient hospitalization to see the dynamic prediction of total charges, via interactive sessions. The R2 value of...
Wind energy is supplying an increasing proportion of demand in the electrical grid. An accompanied problem is that the operational reliability of the power system is affected by the inherent uncertainty and stochastic variation of wind generation which also leads to the wind power forecasts of low accuracy. Therefore, the point prediction of wind power produced by a traditional deterministic forecasting...
It has been shown that unsupervised outlier detection methods can be adapted to the one-class classification problem. In this paper, we focus on the comparison of oneclass classification algorithms with such adapted unsupervised outlier detection methods, improving on previous comparison studies in several important aspects. We study a number of one-class classification and unsupervised outlier detection...
An accurate measurement of the solar irradiance is of importance for evaluating and developing of solar renewable energy systems. However, devices for solar irradiance sensing (e.g. pyranometers and pyrheliometers) are usually expensive and difficult to calibrate. In this paper, a low-cost soft-sensor, implemented with a solar cell, is proposed for real-time estimation of solar irradiance. It applies...
This paper focuses on the use of different multi-step prediction techniques for long-term prognosis of the Lithium-ion batteries condition. Various inductive algorithms including adaptive neuro-fuzzy inference systems, random forests, and group method of data handling are used along with three strategies for multi-step prediction and prognosis. These prediction strategies including iterative, direct,...
Remaining Useful Life (RUL) prediction plays a critical part in many battery-powered applications. Statistical filter, i.e., particle filter (PF) is widely used to predict RUL with various models as well as its uncertainty representation. However, PF commonly used suffers from the lack of poor adaption of long-term prediction and iterative prediction. This disadvantage may further reduce the RUL estimation...
In this paper we propose a new method for finding approximate solutions of ISLAE, by bringing it to “saturated block” using a procedure of reduction. The method is based on the analysis of the properties of solutions ISLAE and on the analysis of the properties of interval models constructed on the basis of these solutions.
One of the standard methods in a verification of predictive models is a cross validation. In this paper, we examined prediction stability of simple learning set of rules classifier under the k-fold cross validation. We described a class of rules that can pass the k-fold cross validation with zero or a very low variance in accuracy of prediction. The lossless prediction of correct/incorrect assignment...
Finite Control Set Model Predictive Control (FCS-MPC) allows to deal with non-linearities of the system and obtain a fast dynamic response. Therefore FCS-MPC is a good alternative to govern complex power converters or when fast transient operation is required. The main drawback of FCS-MPC is the performance obtained during the steady state, the main reason resides in the poor temporal resolution of...
In recent years, a strong interest has been given to web usage prediction and recommendation methods to improve e-commerce, search engines and other online applications. There have been various efforts carried out in this field, particularly focused on using recordings of web user interactions with websites. In this context, our research focuses on developing a novel approach for web prediction and...
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