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Community detection model for dynamic networks based on hidden Markov model and evolutionary algorithm
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Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over time. Here, we adopt a new perspective towards detecting the evolution of community structures. The proposed method realizes the decomposition of the problem into three essential components; searching in: intra-community connections, inter-community connections, and community evolution. A multi-objective optimization problem is defined to account for the different intra and inter community structures. Further, we formulate the community evolution problem as a Hidden Markov Model in an attempt to dexterously track the most likely sequence of communities. Then the new model, called Hidden Markov Model-based Multi-Objective evolutionary algorithm for Dynamic Community Detection (HMM-MODCD), uses a multi-objective evolutionary algorithm and Viterbi algorithm for formulating objective functions and providing temporal smoothness over time for clustering dynamic networks. The performance of the proposed algorithm is evaluated on synthetic and real-world dynamic networks and compared against several state-of-the-art algorithms. The results clearly demonstrate the effectiveness of the proposed algorithm to outperform other algorithms.

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Publication Date
Tue Dec 01 2009
Journal Name
2009 7th International Conference On Information, Communications And Signal Processing (icics)
The effect of traffic load on using XCAST based routing protocol in wireless ad hoc networks
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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Assessing road networks properties based on GIS techniques: Al-Karrada Region/Baghdad as a case study
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Transportability refers to the ease with which people, goods, or services may be transferred. When transportability is high, distance becomes less of a limitation for activities. Transportation networks are frequently represented by a set of locations and a set of links that indicate the connections between those places which is usually called network topology. Hence, each transmission network has a unique topology that distinguishes its structure. The most essential components of such a framework are the network architecture and the connection level. This research aims to demonstrate the efficiency of the road network in the Al-Karrada area which is located in the Baghdad city. The analysis based on a quantitative evaluation using graph th

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Publication Date
Wed Apr 10 2019
Journal Name
Engineering, Technology & Applied Science Research
Content Based Image Clustering Technique Using Statistical Features and Genetic Algorithm
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Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

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Publication Date
Sat Oct 19 2024
Journal Name
Iraqi Statisticians Journal
Forecasting Gold prices by hybrid ANFIS-based algorithm
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In this article, the high accuracy and effectiveness of forecasting global gold prices are verified using a hybrid machine learning algorithm incorporating an Adaptive Neuro-Fuzzy Inference System (ANFIS) model with Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO). The hybrid approach had successes that enabled it to be a good strategy for practical use. The ARIMA-ANFIS hybrid methodology was used to forecast global gold prices. The ARIMA model is implemented on real data, and then its nonlinear residuals are predicted by ANFIS, ANFIS-PSO, and ANFIS-GWO. The results indicate that hybrid models improve the accuracy of single ARIMA and ANFIS models in forecasting. Finally, a comparison was made between the hybrid foreca

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Publication Date
Wed Mar 13 2019
Journal Name
Political Sciences Journal
Community composition of India and its impact on national unity
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India is today the largest democratic state in the Third World and has been able to maintain its national unity in the near future. The history of Indian civilization is more than 5,000 years old. It has achieved its heritage, culture, philosophy, traditions, national unity and unity and has taken its place among nations seeking progress and progress. Which are still visible to the present day, because of their history of civilization and achievements, and the fusion of cultures of invading peoples over the centuries with the culture of diverse Indian society, but despite being a secular state, Has put into place through its governments various forms of exclusion and marginalization towards the people of India, especially Muslims, and th

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Publication Date
Sat Jul 22 2023
Journal Name
Journal Of Engineering
Multiwavelet based-approach to detect shared congestion in computer networks
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Internet paths sharing the same congested link can be identified using several shared congestion detection techniques. The new detection technique which is proposed in this paper depends on the previous novel technique (delay correlation with wavelet denoising (DCW) with new denoising method called Discrete Multiwavelet Transform (DMWT) as signal denoising to separate between queuing delay caused by network congestion and delay caused by various other delay variations. The new detection technique provides faster convergence (3 to 5 seconds less than previous novel technique) while using fewer probe packets approximately half numbers than the previous novel technique, so it will reduce the overload on the network caused by probe packets.

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Publication Date
Tue Mar 30 2021
Journal Name
Wasit Journal Of Computer And Mathematics Science
Dynamic Data Replication for Higher Availability and Security
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The paradigm and domain of data security is the key point as per the current era in which the data is getting transmitted to multiple channels from multiple sources. The data leakage and security loopholes are enormous and there is need to enforce the higher levels of security, privacy and integrity. Such sections incorporate e-administration, long range interpersonal communication, internet business, transportation, coordinations, proficient correspondences and numerous others. The work on security and trustworthiness is very conspicuous in the systems based situations and the private based condition. This examination original copy is exhibiting the efficacious use of security based methodology towards the execution with blockchain

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Publication Date
Sun Mar 01 2026
Journal Name
Case Studies In Thermal Engineering
Dynamic thermal modelling of energy storage unit based on PCM under single or two-phase flow conditions
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Phase change materials are extensively studied for use in low-, mid-, and high-temperature applications due to their melting and solidification temperatures, latent heat, and thermophysical properties. This work aims to explore the energy stored, or released and their duration for the energy storage unit formed of a phase change material surrounding a tube within which a hot or cold, single or Two-Phase fluid flows, serving as a heat source or sink. The 3D axial transient thermal analysis of the energy storage unit is performed using the finite element method via a MATLAB-developed computer program. The effects of single- or Two-Phase fluid flow on temperature distribution, solidification, melting duration, and energy stored within phase ch

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Publication Date
Wed Oct 21 2015
Journal Name
Integrated Journal Of Engineering Research And Technology
A HYBRID CUCKOO SEARCH AND BACK-PROPAGATION ALGORITHMS WITH DYNAMIC LEARNING RATE TO SPEED UP THE CONVERGENCE (SUBPL) ALGORITHM
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BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

Publication Date
Sat Nov 01 2014
Journal Name
International Journal Of Basic And Applied Sciences
A reliable iterative method for solving the epidemic model and the prey and predator problems
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In the present article, we implement the new iterative method proposed by Daftardar-Gejji and Jafari (NIM) [V. Daftardar-Gejji, H. Jafari, An iterative method for solving nonlinear functional equations, J. Math. Anal. Appl. 316 (2006) 753-763] to solve two problems; the first one is the problem of spread of a non-fatal disease in a population which is assumed to have constant size over the period of the epidemic, and the other one is the problem of the prey and predator. The results demonstrate that the method has many merits such as being derivative-free, overcome the difficulty arising in calculating Adomian polynomials to handle the nonlinear terms in Adomian Decomposition Method (ADM), does not require to calculate Lagrange multiplier a

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