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Finding Best Clustering For Big Networks with Minimum Objective Function by Using Probabilistic Tabu Search
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     Fuzzy C-means (FCM) is a clustering method used for collecting similar data elements within the group according to specific measurements. Tabu is a heuristic algorithm. In this paper, Probabilistic Tabu Search for FCM implemented to find a global clustering based on the minimum value of the Fuzzy objective function. The experiments designed for different networks, and cluster’s number the results show the best performance based on the comparison that is done between the values of the objective function in the case of using standard FCM and Tabu-FCM, for the average of ten runs.

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Publication Date
Thu Dec 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
solving linear fractional programming problems (LFP) by Using denominator function restriction method and compare it with linear transformations method
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Abstract

The use of modern scientific methods and techniques, is considered important topics to solve many of the problems which face some sector, including industrial, service and health. The researcher always intends to use modern methods characterized by accuracy, clarity and speed to reach the optimal solution and be easy at the same time in terms of understanding and application.

the research presented this comparison between the two methods of solution for linear fractional programming models which are linear transformation for Charnas & Cooper , and denominator function restriction method through applied on the oil heaters and gas cookers plant , where the show after reac

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Fuzzy Multi-Objective Capacitated Transportation Problem with Mixed Constraints using different forms of membership functions
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In this research, the problem of multi- objective modal transport was formulated with mixed constraints to find the optimal solution. The foggy approach of the Multi-objective Transfer Model (MOTP) was applied. There are three objectives to reduce costs to the minimum cost of transportation, administrative cost and cost of the goods. The linear membership function, the Exponential membership function, and the Hyperbolic membership function. Where the proposed model was used in the General Company for the manufacture of grain to reduce the cost of transport to the minimum and to find the best plan to transfer the product according to the restrictions imposed on the model.

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
New and Existing Approaches Reviewing of Big Data Analysis with Hadoop Tools
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Everybody is connected with social media like (Facebook, Twitter, LinkedIn, Instagram…etc.) that generate a large quantity of data and which traditional applications are inadequate to process. Social media are regarded as an important platform for sharing information, opinion, and knowledge of many subscribers. These basic media attribute Big data also to many issues, such as data collection, storage, moving, updating, reviewing, posting, scanning, visualization, Data protection, etc. To deal with all these problems, this is a need for an adequate system that not just prepares the details, but also provides meaningful analysis to take advantage of the difficult situations, relevant to business, proper decision, Health, social media, sc

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Publication Date
Mon Apr 17 2023
Journal Name
Wireless Communications And Mobile Computing
A Double Clustering Approach for Color Image Segmentation
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One of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Engineering
Determination of Best Location for Elevated Tank in Branched Network
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The research focuses on determination of best location of high elevated tank using the required head of pump as a measure for this purpose. Five types of network were used to find the effect of the variation in the discharge and the node elevation on the best location. The most weakness point was determined for each network. Preliminary tank locations were chosen for test along the primary pipe with same interval distance. For each location, the water elevation in tank and pump head was calculated at each hour depending on the pump head that required to achieve the minimum pressure at the most weakness point. Then, the sum of pump heads through the day was determined. The results proved that there is a most economical lo

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Publication Date
Mon Jun 17 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Dynamic Channel Assignment Using Neural Networks
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This paper presents a proposed neural network algorithm to solve the shortest path problem (SPP) for communication routing. The solution extends the traditional recurrent Hopfield architecture introducing the optimal routing for any request by choosing single and multi link path node-to-node traffic to minimize the loss. This suggested neural network algorithm implemented by using 20-nodes network example. The result shows that a clear convergence can be achieved by 95% valid convergence (about 361 optimal routes from 380-pairs). Additionally computation performance is also mentioned at the expense of slightly worse results.

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Publication Date
Wed Sep 01 2010
Journal Name
Journal Of Economics And Administrative Sciences
Finding Mixture Weibull Distribution
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In this paper a new idea was introduced which is finding a new distribution from other distributions using mixing parameters; wi  where  0 < wi < 1 ­and . Therefore we can get many mixture distributions with a number of parameters. In this paper I introduced the idea of a mixture Weibull distribution which is produced from mixing two Weibull distributions; the first with two parameters, the scale parameter , and the shape parameter,  and the second also has the scale parameter , and the shape parameter,  in addition to the location parameter, . These two distributions were mixed using a new parameter which is the mixing parameter w which represents the proportion

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Publication Date
Fri Oct 01 2010
Journal Name
2010 Ieee Symposium On Industrial Electronics And Applications (isiea)
Distributed t-way test suite data generation using exhaustive search method with map and reduce framework
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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
F-Compact operator on probabilistic Hilbert space
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This paper deals with the F-compact operator defined on probabilistic Hilbert space and gives some of its main properties.

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