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Data Missing Solution Using Rough Set theory and Swarm Intelligence
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This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estimation through working with rough set theory. The results obtained from most code sets show that Bees algorithm better than ID3 in decreasing the number of extracted rules without affecting the accuracy and increasing the accuracy ratio of null values estimation, especially when the number of null values is increasing

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Partial substitution of Zn Effects on the Structural and Electrical Properties of High Temperature Hg<sub>0.95</sub>Ag<sub>0.05</sub>Ba<sub>2</sub>Ca<sub>2</sub>Cu<sub>3</sub>O<sub>8+δ</sub> Superconductors
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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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Publication Date
Wed Mar 01 2023
Journal Name
Baghdad Science Journal
A Characterization of Maximal Outerplanar-Open Distance Pattern Uniform Graphs
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Let A ⊆ V(H) of any graph H, every node w of H be labeled using a set of numbers; , where d(w,v) denotes the distance between node w and the node v in H, known as its open A-distance pattern. A graph H is known as the open distance-pattern uniform (odpu)-graph, if there is a nonempty subset A ⊆V(H) together with  is the same for all . Here  is known as the open distance pattern uniform (odpu-) labeling of the graph H and A is known as an odpu-set of H. The minimum cardinality of vertices in any odpu-set of H, if it exists, will be known as the odpu-number of the graph H. This article gives a characterization of maximal outerplanar-odpu graphs. Also, it establishes that the possible odpu-number of an odpu-maximal outerplanar graph i

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Publication Date
Sun Sep 02 2012
Journal Name
Baghdad Science Journal
New Fuzzy Normed Spaces
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In this paper the research introduces a new definition of a fuzzy normed space then the related concepts such as fuzzy continuous, convergence of sequence of fuzzy points and Cauchy sequence of fuzzy points are discussed in details.

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Publication Date
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
Tadpole Domination in Graphs
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A new type of the connected domination parameters called tadpole domination number of a graph is introduced. Tadpole domination number for some standard graphs is determined, and some bounds for this number are obtained. Additionally, a new graph, finite, simple, undirected and connected, is introduced named weaver graph. Tadpole domination is calculated for this graph with other families of graphs.

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
Hn-Domination in Graphs
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The aim of this article is to introduce a new definition of domination number in graphs called hn-domination number denoted by . This paper presents some properties which show the concepts of connected and independent hn-domination. Furthermore, some bounds of these parameters are determined, specifically, the impact on hn-domination parameter is studied thoroughly in this paper when a graph is modified by deleting or adding a vertex or deleting an edge.

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Interdisciplinary Mathematics
On ⱨ - supra open sets in supra topological spaces
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The significance fore supra topological spaces as a subject of study cannot be overstated, as they represent a broader framework than traditional topological spaces. Numerous scholars have proposed extension to supra open sets, including supra semi open sets, supra per open and others. In this research, a notion for ⱨ-supra open created within the generalizations of the supra topology of sets. Our investigation involves harnessing this style of sets to introduce modern notions in these spaces, specifically supra ⱨ - interior, supra ⱨ - closure, supra ⱨ - limit points, supra ⱨ - boundary points and supra ⱨ - exterior of sets. It has been examining the relationship with supra open. The research was also enriched with many

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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
The Importance of Strategic Orientation Dimensions in the Iraqi National Security Service: An Analytical Study
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The current research aims to identify the level of strategic orientation and its dimensions (vision, mission, goals, and values) in the Iraqi National Security Service (INSS). The researchers followed the descriptive analytical approach as one of the forms of analysis and organized scientific interpretation to describe a specific phenomenon or problem, adopting the form questionnaire being the main source in collecting data and preparing for this. Based on the program of the Statistical Package of Social Sciences (SPSS 26) to analyze the data and come up with the final research results to identify the opinions of the intended sample on the subject of research, and the questionnaire of (20) paragraphs included the search variable, and was

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Publication Date
Mon Jun 30 2008
Journal Name
Iraqi Journal Of Science
On the Greedy Ridge Function Neural Networks for Approximation Multidimensional Functions
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The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

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Publication Date
Sun Oct 01 2017
Journal Name
International Journal Of Scientific & Engineering Research
Horizontal Fragmentation for Most Frequency Frequent Pattern Growth Algorithm
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Abstract: Data mining is become very important at the present time, especially with the increase in the area of information it's became huge, so it was necessary to use data mining to contain them and using them, one of the data mining techniques are association rules here using the Pattern Growth method kind enhancer for the apriori. The pattern growth method depends on fp-tree structure, this paper presents modify of fp-tree algorithm called HFMFFP-Growth by divided dataset and for each part take most frequent item in fp-tree so final nodes for conditional tree less than the original fp-tree. And less memory space and time.

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