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.
Data Clustering in Data Mining is a domain which never gets out of focus. Clustering a data was always an easy task but achieving the required accuracy, precision and performance was never so easy. K means being an archaic clustering algorithm got tested and experimented thousands of times with variety of datasets and other combination of algorithm due to its robustness and simplicity but what this...
Internet of Things (IoT) is a new network paradigm that allows the virtual presence of physical objects in our life. The main idea of IoT is origin from equipping daily life objects with embedded devices. Meanwhile, due to the low cost and high availability of sensor devices, wireless sensor networks (WSNs) have a great role in overspreading of IoT. This paper presents a new routing algorithm in order...
The limited number of resources in Wireless sensor Networks (WSNs) and long communication distance between sensors and base station causes high energy consumption and consequently reduce the network lifetime. Therefore one of the important parameters in these networks is the optimized energy consumption. One way to reduce the energy consumption is to cluster the network. In this study, a dynamic clustering...
Social Media produces petabytes of data in the form of audio, video, texts, comments, expressions, and emotions. ETL technologies failed to configure the large amount of data and its relevance to the distributed data. Therefore, it's important to analyse the racks of datasets to find out the suitable similarities. Hence, clustering is one of the required operations for the datasets. As the dataset...
Since last decade, our eye witnessed proofs that Wireless Sensor Networks (WSNs) have been used in many areas like health care, agriculture, defense, military, disaster hit areas and so on. The key parameters that play a major role in designing a protocol for WSNs are its energy efficiency and computational feasibility, as sensor nodes are resource constrained. Variation in sensor nodes distance from...
Utilization of machine learning algorithms in time-series data analysis is crucial to effective decision making in today's dynamic and competitive environment. One data type of growing interest is the electricity consumer load profile (LP) data. Owing to advances in the smart grid, immense amount of LP data became available to policymakers as potential to improving the electricity sector. Due to the...
In order to improves the real-time analysis of the profitability of enterprises, this paper provided a model of insurance risk rating based on neural network. Through learning and clustering features of customers, customers are divided into seven categories, and the results show the model is very good to achieve the user found and early warning effectively.
In today's world Wireless Sensor Networks (WSNs) has gained a lot of recognition because of its wide-ranging areas of applications. Sensor nodes in WSNare connected to each other by networks, mainly powered by a battery source. These sensor nodes have lesser amount of power and computational capabilities. Typically, sensor nodes are deployed in remote areas where replacement of their batteries once...
Persons are often asked to provide information about themselves. These data are very heterogeneous and result in as many “profiles” as contexts. Sorting a large amount of profiles from different contexts and assigning them back to a specific individual is quite a difficult problem. Semantic processing and machine learning are key tools to achieve this goal. This paper describes a framework to address...
We consider the problem of automatic construction of algorithms for recognition of abnormal behavior segments in phase trajectories of dynamic systems. The recognition algorithm is trained on a set of trajectories containing normal and abnormal behavior of the system. The exact position of segments corresponding to abnormal behavior in the trajectories of the training set is unknown. To construct...
Genetic Algorithm (GA) is an effective method for solving Traveling Salesman Problems (TSPs), nevertheless, the Classical Genetic Algorithm (CGA) performs poor effect for large-scale traveling salesman problems. For conquering the problem, this paper presents two improved genetic algorithms based on clustering to find the best results of TSPs. The main process is clustering, intra-group evolution...
Routing plays a major role in increasing the energy efficiency of a wireless sensor network. In a cluster based wireless sensor network, cluster head can forward the data to the base station either directly or indirectly (multi-hoping). However, in multi-hop routing energy saving is more as compared to direct transmission. Further, the selection of energy efficient routing schedules helps in increasing...
In this paper we demonstrate that some recent clustering techniques do not produce sensible clusters and fail to discover knowledge from underlying data sets. Sometimes, they obtain a huge number of clusters from few records and sometimes they obtain only two clusters from many records, where one cluster contains one record and the other cluster contains all remaining records. Interestingly, these...
In this paper we propose a Genetic Algorithm-based clustering technique called GMC that produces high-quality chromosomes in the initial population. The proposed technique also introduces two phases of crossover operation with extensive chromosomes generation aiming to produce high-quality offspring chromosomes and prevent degeneracy. The proposed technique also introduces three steps of mutation...
Clustering has been one of the most commonly used strategies for maximizing the lifetime of wireless sensor networks (WSNs). Clustering in WSNs is the process of grouping the sensors based on some criteria and optimal clustering in WSNs is known to be a NP-Hard problem. Evolutionary algorithms (e.g. genetic algorithm) have been extensively utilized for addressing this problem. In this paper, energy...
In this work, performance analysis of Clustering based Genetic Algorithm (CGA) proposed in the literature has been undertaken. The proposed CGA on which the performance analysis of this paper is based involve the use of two centroids based clustering technique as a new method of chromosomes selection at the reproduction stage in a typical Genetic Algorithm. Population Control and Polygamy mating techniques...
Data mining and machine learning are becoming the most interesting research areas and increasingly popular in health organizations. The hidden patterns among patients data can be extracted by applying data mining. The techniques and tools of data mining are very helpful as they provide health care professionals with significant knowledge toward a decision. Researchers have shown several utilities...
The increasing influence of social media and enormous participation of users creates new opportunities to study human social behavior along with the capability to analyze large amount of data streams. One of the interesting problems is to distinguish between different kinds of users, for example users who are leaders and introduce new issues and discussions on social media. Furthermore, positive or...
Test data generation is the process of generating a set of input data for testing software. High quality test data helps to improve the error finding ability of software in every stages of the development life cycle. The most critical activity in software testing is the generation of test data. In existing approach, coverage based testing techniques like statement coverage, branch coverage are applied...
There are variety of methods available to solve multi-objective optimization problems, very few utilizes criterion linkage between data objects in the searching phase, to improve final result. This article proposes an evolutionary clustering algorithm for multi-objective optimization. This paper aims to identify more relevant features based on criterion knowledge from the given data sets and also...
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.