The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this empirical study we develop forecasting models for electricity demand using publicly available data and three models based on machine learning algorithms. It compares accuracy of these models using different evaluation metrics. The data consist of several measurements and observations related to the electricity market in Turkey from 2011 to 2016. It is available in different time granularities...
In the big data era, machine learning has become an increasingly popular approach for data processing. Data could be in various forms, such as text, images, audios, videos and signals. The essence of machine learning is to learn any patterns from features of data. In the above types of data, the number of features is massively high, which could result in the presence of a large number of irrelevant...
A decision tree is an important classification technique in data mining classification. Decision trees have proved to be valuable tools for the classification, description, and generalization of data. J48 is a decision tree algorithm which is used to create classification model. J48 is an open source Java implementation of the C4.5 algorithm in the Weka data mining tool. In this paper, we present...
Implementing higher voltages in vehicles like 48V mild hybrid or full-hybrid enables CO2 reduction and weight savings. However, the increase in the voltage demands an accurate and robust protection system again potential fault conditions. Series arc is one of the fault conditions which needs to be detected and addressed before the benefits of using higher voltages in vehicle can be fully realized...
Categorical data exist in many domains, such as text data, gene sequences, or data from Census Bureau. While such data are easy for human interpretation, they cannot be directly used by many classification methods, such as support vector machines and others, which require underlying data to be represented in a numerical format. To date, most existing learning methods convert categorical data into...
Transfer learning has attracted more and more attention, and many scholars proposed some useful strategies. Boosting is the main strategy for transfer learning. In boosting, resampling is preferred over reweighting, and it can be applied to any base learner. In this paper, we propose a weighted-resampling method for transfer learning, called TrResampling. Firstly, resampling is applied to the data...
Rapid urbanization has generated a large number of construction land problems in China, such as the idleness and illegal use of land. Whereas most methods have focused on the discovery of idle construction land by spatial overlay analysis, far less attention has been paid to the prediction of the idle construction land in advance. In this paper, a new method based on the Gradient Boosting Machine...
Network Traffic Classification carries great importance for both internet service providers (ISPs) and quality of services (QoSs) management. During the last two decades, a lot of machine learning models have been proposed and applied on different types of real time applications to classify their real time traffic and obtain very proficient accuracy results. However, no research has been done on WeChat...
Classification is the process of developing a model which assigns records in a collection to predefined categories or classes. Various algorithms like K Nearest Neighbour, Naive Bayes, Support Vector Machine, and C4.5 have been implemented to develop a classification model. The ultimate goal of a classifier is to accurately predict the target class for a given set of input data. The process of classification...
Email spam is an increasing problem because it disrupting and time consuming for user, since the easy and cheap of sending email. Email Spam filtering can be done with a binary classification with machine learning as classifier. To date, email spam detection still challenging since the email spam still happens a lot and the detection still need improvement. Decision Tree (DT) is one of famous classifier...
Decision trees are common algorithms in machine learning. Traditionally, these algorithms make trees recursively and at each step, they inspect data to induce the part of the tree. However decision trees are famous for their instability and high variance in error. In this paper a solution which adds error correction rule to a traditional decision tree algorithm is examined. In fact an algorithm which...
We use supervised machine learning algorithms (i.e., Decision Trees, Random Forest, and K-nearest Neighbors) to predict performance characteristics such as runtime and IO traffic of batch jobs on high-end clusters, using only user job scripts as input. We show that decision trees outperform other algorithms and accurately predict the runtime of 73% of jobs within a error tolerance of 10 minutes, which...
a rule based system is a special type of expert system which consists of a set of rules. In practice, rule based systems can be built by using expert knowledge or learning from real data. Due to the vast and increasing size of data, the latter approach has become quite popular for building rule based systems. In particular, rule based systems can be built through use of rule learning algorithms, which...
A diamond adsorption detecting system based on machine learning is presented in this paper. The paper describes the system from the perspective of hardware and software design, and presents the image processing and machine learning algorithms applied in the system. The hardware includes three major parts — the camera, light source and support platform. The software includes modules of image acquisition,...
A grade crossing is defined as an intersection between a roadway and a railway at the same elevation or grade. Multiple new prevention measures have been implemented to reduce the number of train-vehicle collisions; however, crossing safety is still a major issue as accidents still frequently occur. The push for data-driven models to evaluate risks at grade crossings has also increased to keep up...
Malware is a computer program or a piece of software that is designed to penetrate and detriment computers without owner's permission. There are different malware types such as viruses, rootkits, keyloggers, worms, trojans, spywares, ransomware, backdoors, bots, logic bomb, etc. Volume, Variant and speed of propagation of malwares are increasing every year. Antivirus companies are receiving thousands...
Wearable watches provide very useful linear acceleration information that can be use to detect falls. Howeverfalls not from a standing position are difficult to spot amongother normal activities. This paper describes methods, basedon pattern recognition using machine learning, to improve thedetection of "soft falls". The values of the linear accelerometersare combined in a robust vector...
Fingerprinting based positioning is commonly used for indoor positioning. In this method, initially a radio map is created using Received Signal Strength (RSS) values that are measured from predefined reference points. During the positioning, the best match between the observed RSS values and existing RSS values in the radio map is established as the predicted position. In the positioning literature,...
The aim of this paper is to present the algorithms that were developed for detecting human in the conditions of overlapping and non-overlapping. Overlapping means when person is not fully visible in the image and occluded by another person at the front or right/left side. In order to achieve this goal, three steps were implemented. The algorithms were implemented in C++ with the help of Open Source...
Extreme learning machine (ELM) is an efficient learning algorithm which can be easily used with least human intervene. But when ELM is applied as multiclass classifier, the results of some classes are not satisfactory and it's hard to adjust the parameters for these classes without affecting other classes. To overcome these limitations, a novel method is proposed. In proposed approach, binary ELM...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.