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Hybrid canonical genetic algorithm and steepest descent algorithm for optimizing likelihood estimators of ARMA (1, 1) model
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This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conclude that (hGA) can give good estimators (phi(1),theta(1)) of ARMA(1,1)parameters and more reliable than estimators obtained by cGA and SDA algorithm

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Publication Date
Thu Dec 05 2019
Journal Name
Advances In Intelligent Systems And Computing
An Enhanced Evolutionary Algorithm for Detecting Complexes in Protein Interaction Networks with Heuristic Biological Operator
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Publication Date
Sat Aug 25 2012
Journal Name
Wireless Personal Communications
Multi-Objective Evolutionary Algorithm Based on Decomposition for Energy Efficient Coverage in Wireless Sensor Networks
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Publication Date
Sun Mar 01 2020
Journal Name
Computer Networks
An improved multi-objective evolutionary algorithm for detecting communities in complex networks with graphlet measure
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Publication Date
Sun Jul 01 2012
Journal Name
2012 International Symposium On Innovations In Intelligent Systems And Applications
Edge detection for fast block-matching motion estimation to enhance Mean Predictive Block Matching algorithm
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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Evaluation Tv- Image Quality for Different Cable Signal Transmission Resistance Based on Contrast Edge Algorithm
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Some degree of noise is always present in any electronic device that
transmits or receives a signal . For televisions, this signal i has been to s the
broadcast data transmitted over cable-or received at the antenna; for digital
cameras, the signal is the light which hits the camera sensor. At any case, noise
is unavoidable. In this paper, an electronic noise has been generate on
TV-satellite images by using variable resistors connected to the transmitting cable
. The contrast of edges has been determined. This method has been applied by
capturing images from TV-satellite images (Al-arabiya channel) channel with
different resistors. The results show that when increasing resistance always
produced higher noise f

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Publication Date
Wed Feb 01 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

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Publication Date
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

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Publication Date
Fri Nov 01 2019
Journal Name
Journal Of Global Pharma Technology
Synthesis and Phase Transition Study of New Mesogence Derived from 1, 4-Phenylenediamine
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This work include synthesized and characterization the compound [I] by reaction 1,4-phenylenediamine with chloro acetic acid then this compound reaction with methanol in present sulfuric acid to synthesized ester compound [II] after that reaction with hydrazine hydrate to synthesized acide hydrazide [III] and the later compound reaction with substituted acetophenone[IV]n to synthesized substituted acetophenone hydrazones[V-XI]. In addition synthesized4-formylpyrazole derivatives [XIIXVIII] via cyclisation substituted acetophenone hydrazones [V-XI] with Vilsmeier-Haack reagent DMF/POCl3. The compounds characterized by melting points, FTIR, 1HNMR and mass spectroscopy. The mesomorphic behavior studied by using polarized optical microscopy and

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Publication Date
Wed May 12 2021
Journal Name
Annals Of The Romanian Society For Cell Biology
Role of Serum Omentin-1 and Bone Metabolism Markersin Osteoporosis among Postmenopausal Women
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menopause is the most common cause of accelerated bone loss in women. Omentin-1 is secreted by the visceral adipose tissue and it isdonated in the regulation of bone metabolism in postmenopausal women which is related with decreased bone mineral density. The current study aims to investigate the role of serum omentin-1and some bone metabolism markers in osteoporosis among postmenopausal Iraqi women. This study was performedin the Rheumatology and Rehabilitation Unit, Baghdad Teaching Hospital/ Baghdad medical city, during the period from November 2019 to July 2020 with a total of 60 postmenopausal women(30 with osteoporosis and 30 without osteoporosis), their ages ranged from 52 to 62 years. They were compared with 30 healthy premenopausal

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Publication Date
Mon Jan 01 2018
Journal Name
Journal Of Central European Agriculture
Biofertilizer (EM-1) effect on growth and yield of three bread wheat cultivars
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Farmers keep trying to avoid using chemical fertilizer without losing high yield. A field experiment was conducted in the fields of Agriculture College, University of Baghdad during winter seasons of 2015 and 2016 to investigate the response of three bread wheat (Triticum aestivum L.) cultivars (Ibaa99, Abu-Ghraib3 and Buhooth22) to the frequency of spraying with biofertilizer (EM-1) (one time at tillering stage, twice at tillering and stem elongation stages and three times at tillering, stem elongation and booting stages) in addition to the control (without spraying), to the increase of grain yield. Randomized complete block design (RCBD), in split plots arrangement and four replications, was used. Spraying treatments were placed as main p

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