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Modified Kohonen network algorithm for selection of the initial centres of Gustafson-Kessel algorithm in credit scoring
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Credit risk assessment has become an important topic in financial risk administration. Fuzzy clustering analysis has been applied in credit scoring. Gustafson-Kessel (GK) algorithm has been utilised to cluster creditworthy customers as against non-creditworthy ones. A good clustering analysis implemented by good Initial Centres of clusters should be selected. To overcome this problem of Gustafson-Kessel (GK) algorithm, we proposed a modified version of Kohonen Network (KN) algorithm to select the initial centres. Utilising similar degree between points to get similarity density, and then by means of maximum density points selecting; the modified Kohonen Network method generate clustering initial centres to get more reasonable clustering results. The comparative was conducted using three credit scoring datasets: Australian, German and Taiwan. Internal and external indexes of validity clustering are computed and the proposed method was found to have the best performance in these three data sets.

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Publication Date
Wed Jan 01 2020
Journal Name
International Conference Of Numerical Analysis And Applied Mathematics Icnaam 2019
Functionalized multi-walled carbon nanotubes network sensor for NO2 gas detection at room temperature
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Publication Date
Tue Dec 16 2008
Journal Name
Journal Of Planner And Development
The relationship between the uses of land and the network of movement and roads (study area, Najaf city)
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The interaction in the city is reflected in the movement of people motivated by their activities and their economic and social goals, which include many variables subject to the planning process in the interpretation of this movement and the mapping of trends of transport intensity through the concept of transport function and its functional relationships with the uses of the earth in the sustainability and effectiveness of the movement of transport and Economic activity and population movement. Transport planners are concerned with the requirements of land use, which are linked to and included in the transport planning process as a factor for the future transport needs. There is a strong relationship between the transport system

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Spatial Prediction of Monthly Precipitation in Sulaimani Governorate using Artificial Neural Network Models
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ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

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Publication Date
Thu Jun 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Performance Improvement of Neural Network Based RLS Channel Estimators in MIMO-OFDM Systems
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The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Intelligent Congestion Control of 5G Traffic in SDN using Dual-Spike Neural Network
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Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification

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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Engineering
Some Properties of Cement Mortar Modified by Styrene Butadiene Rubber
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This research studies the effect of adding five different percentages of polymer (2, 4, 6, 8, and 10% of cement weight) on cement mortar's fresh and hardened properties, which was cured at laboratory temperature for 7, 14, and 28 days. Workability increases with increasing polymer. The workability value was lowest (25.6 and 29.4) % in mixtures containing 2% and 4% of (SBR). Increasing polymer ratios significantly decreased mechanical properties (compressive and flexural strength). Therefore, the best results were at 2% SBR and 4% SBR at 28 days of age. An inverse relationship was recorded between the increase in SBR ratios and polymer-modified cement mortar's compressive and flexural strength values. In general, the high

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Publication Date
Tue Sep 14 2010
Journal Name
Journal Of Polymers And The Environment
Mechanical and Thermal Properties of PLLA/PCL Modified Clay Nanocomposites
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Poly(L-lactic acid) (PLLA)/poly(caprolactone) (PCL) and two types of organoclay (OMMT) including a fatty amide and ocatdecylamine montmorillonite (FA-MMT and ODA-MMT) were employed to produce polymer nanocomposites by melt blending. Materials were characterized using X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), elemental analysis, scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Mechanical properties were also investigated for these nanocomposites. The nanocomposites showed increasing mechanical properties and thermal stability. XRD results indicated that the materials formed nanocomposites. SEM morphology showed that increasing content of OMMT reduc

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Publication Date
Tue Dec 03 2019
Journal Name
Civil Engineering Journal
Moisture Susceptibility of Asphalt Concrete Pavement Modified by Nanoclay Additive
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Durability of hot mix asphalt (HMA) against moisture damage is mostly related to asphalt-aggregate adhesion. The objective of this work is to find the effect of nanoclay with montmorillonite (MMT) on Marshall properties and moisture susceptibility of asphalt mixture. Two types of asphalt cement, AC(40-50) and AC(60-70) were modified with 2%, 4% and 6% of Iraqi nanoclay with montmorillonite. The Marshall properties, Tensile strength ratio(TSR) and Index of retained strength(ISR) were determined in this work. The total number of specimens was 216 and the optimum asphalt content was 4.91% and 5% for asphalt cement (40-50) and (60-70) respectively. The results showed that the modification of asphalt cement with MMT led to increase Marsh

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Publication Date
Mon Jan 01 2018
Journal Name
Fuel
Wettability of nanofluid-modified oil-wet calcite at reservoir conditions
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Nanofluids, liquid suspensions of nanoparticles (Np), are an effective agent to alter the wettability of oil-wet reservoirs to water-wet thus promoting hydrocarbon recovery. It can also have an application to more efficient carbon storage. We present a series of contact angle (θ) investigations on initially oil-wet calcite surfaces to quantify the performance of hydrophilic silica nanoparticles for wettability alteration. These tests are conducted at typical in-situ high pressure (CO2), temperature and salinity conditions. A high pressure–temperature (P/T) optical cell with a regulated tilted surface was used to measure the advancing and receding contact angles at the desired conditions. The results showed that silica nanofluids can alte

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Publication Date
Fri Aug 13 2021
Journal Name
Neural Computing And Applications
Integration of extreme gradient boosting feature selection approach with machine learning models: application of weather relative humidity prediction
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