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Weather is a key driving factor of electricity demand. During the past five decades, temperature is the most commonly used weather variable in load forecasting models. Although humidity has been discussed in the load forecasting literature, it has not been studied as formally as temperature. Humidity is usually embedded in the form of heat index (HI) or temperature-humidity index. In this paper, we...
Regression analysis is a statistical method widely used in the literature. One of the most common uses of this method is to make a prediction. However, some assumptions must be satisfied in order to use this method properly. Each regression model obtained may not be statistically valid. Models need to meet certain qualifications in order to be valid. There are various regulatory model qualification...
Happiness is supposed to be the ultimate goal of life and hence considered very important in life. Whatever action is done by human being is ultimately to be happy. Aristotle called it the summum bonnum or chief good in life. In recent times people have not become happier than earlier generations even though there is a drastic improvement in technology and lifestyle standards. Increasing narcissism...
This paper compared and evaluated the effects of explanatory power of regression models on predictive performance in component decomposition-based downscaling of coarse scale precipitation products. The regression models applied in this paper include (1) multiple linear regression (MLR), (2) geographically weighted regression (GWR), and (3) random forest (RF). From a case study of spatial downscaling...
The study of cyclist behavior for developing realistic and reliable behavioral models is attracting research focus. Achieving a detailed understanding of cyclist behavior is a cornerstone in building micro-simulation models and ultimately creating a more sustainable transportation system. Cyclist behavior is especially important at traffic intersections due to the exposure to turning and crossing...
Inaccurate line loss predictions leads to additional regulation costs for Transmission System Operators (TSOs) that place energy bids at the day-ahead market to account for these losses. This paper presents a line loss prediction model design, applicable with the TSOs forecast conditions, that can reduce additional expenditure due to inaccurate predictions. The model predicts line losses for the next...
Electricity demand forecasting constitutes a critical process in the operation and planning procedures of power networks that highly affects the decisions of utility providers and energy policy makers. Accurate forecasting is vital in reducing costs, related to excess electricity storage and infrastructures, and achieving enhanced power security and stability. A novel modeling approach for long-term...
Tool condition monitoring is one of the key issues in mechanical micromachining for efficient manufacturing of the micro-parts in several industries. In the present study, a tool condition monitoring system for micro-drilling is developed using a tri-axial accelerometer, a data acquisition and signal processing module and an artificial neural network. Micro-drilling experiments were carried out on...
This paper deals with research of safety performance predictions to allow improved risk control in military. Safety performance is identified as appropriate tool to establish system-wide information on safety which can serve the decision making process on how to manage safety. The information contributes to better understanding of behavioural patterns in the controlled system and the ability to foresee...
Machining parameters influence the energy consumed during machining processes. A reliable prediction model for energy consumption will enable industry to achieving energy saving by optimizing the machining parameters during process planning stage. This paper presents a two-level optimization artificial neural network modelling method to characterizing the relationship between energy consumption and...
Since the performance of educational institutions depends critically on their students, it is imperative that educational institutions deploy an efficient and reliable admission criteria. In the context of Pakistan, a variety of admission criteria has been developed—mostly in isolation—by different universities. Despite the importance of these admission criteria, limited systematic information exists...
Light-weight Self-Compacting Concrete (LWSCC) might be the answer to the increasing construction requirements of slenderer and more heavily reinforced structural elements. However there are limited studies to prove its ability in real construction projects. In conjunction with the traditional methods, artificial intelligent based modeling methods have been applied to simulate the non-linear and complex...
in this study, three models namely the linear coefficient model, the Standard ASTM E2527 and the Sandia National Laboratories model, among some methods of the prediction of maximum power have been adequately selected to investigate the performance of a High concentrator photovoltaic (HCPV) system, upon atmospheric conditions such as the direct normal irradiation DNI, the ambient temperature, the wind...
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...
This paper uses multiple regression analysis method to establish customer' s load regression models, which consider economic indicators, air temperature and rainfall. Furthermore, the proposed models are used to study the forecasting feasibility of the future energy sales and summer peak load demand. The least-squares technique is applied to derive regression models of 34 customer energy sales and...
This study examines the degree to which engineering and science students' personality and demographic characteristics are associated with their leadership practices, an area that few studies have explored. The data was from a sample of 70 students attending two institutions (Massachusetts Institute of Technology [MIT] and the Singapore University of Technology and Design [SUTD]) who participated in...
Feature selection is one of the techniques in machine learning for selecting a subset of relevant features namely variables for the construction of models. The feature selection technique aims at removing the redundant or irrelevant features or features which are strongly correlated in the data without much loss of information. It is broadly used for making the model much easier to interpret and increase...
Correctly predicting the passenger flow of an air route is crucial for the airline company to make sales policy. Because of the uncertainties and data inadequacy in the passenger flow prediction of the civil aviation, regression analysis and a grey prediction method are used for predicting and analyzing the passenger flow of the air route in 2016 based on the data of to-and-fro air route of an airline...
Social influence has been a widely accepted phenomenon in social networks for decades. In this paper, we study influence from the perspective of structure, and focus on the simplest group structure — triad. We analyze two different genres of behavior: Retweeting on Weibo1 and Paying on CrossFire2. We have several intriguing observations from these two networks. First, different internal structures...
This preliminary study investigates feasibility of a running speed based heart rate (HR) prediction. It is basically motivated from the assumption that there is a significant relationship between HR and the running speed. In order to verify the assumption, HR and running speed data from 217 subjects of varying aerobic capabilities were simultaneously collected during an incremental treadmill exercise...
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