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ijp-1015
Development and Assessment of Feed Forward Back Propagation Neural Network Models to Predict Sunshine Duration
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         The duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmospheric pressure were used as input parameters in order to obtain the daily average of sunshine duration (SD) as the output. The eight-year data were divided into two categories. The first category covers whole years (annually) and the second category is seasonal. To recognize and assess the influence of different input parameters on sunshine duration, six models of ANN have been evolved. The findings showed that in the annual models, the outcomes of RMSE, MAE and R for the model with input parameters (Month, Cloud Level and Average Temperature) were the best results 1.82, 1.175 and 0.89, respectively. As for the season models, the outcomes of RMSE, MAE and R for the autumn season were the best results 1.450, 1.009 and 0.94, respectively. Accordingly, the performance of the artificial neural network is considerably effective in predicting the sunshine duration.

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Publication Date
Fri Oct 02 2009
Journal Name
Noise And Health
Expert system to predict effects of noise pollution on operators of power plant using neuro-fuzzy approach
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Ration power plants, to generate power, have become common worldwide. One such one is the steam power plant. In such plants, various moving parts of heavy machines generate a lot of noise. Operators are subjected to high levels of noise. High noise level exposure leads to psychological as well physiological problems; different kinds of ill effects. It results in deteriorated work efficiency, although the exact nature of work performance is still unknown. To predict work efficiency deterioration, neuro-fuzzy tools are being used in research. It has been established that a neuro-fuzzy computing system helps in identification and analysis of fuzzy models. The last decade has seen substantial growth in development of various neuro-fuzzy systems

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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of Food Process Engineering
Artificial intelligence‐based modeling of novel non‐thermal milk pasteurization to achieve desirable color and predict quality parameters during storage
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Abstract<sec><label></label><p>This study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (<italic>p</italic> > 0.05) for lightness (<italic>L</italic>*), redness‐greenness (<italic>a</italic>*), yellowness‐blueness (<italic>b</italic>*), total color differences (∆<italic>E</italic>), hue angle (<italic>h</italic></p></sec> ... Show More
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Publication Date
Sat Feb 01 2025
Journal Name
Iop Conference Series: Earth And Environmental Science
Chitosan as an Aflatoxin Inhibitor in Local Fish Feed
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Abstract<p>The current research attempts to find a feed additive that enhances fish growth and eliminate toxins generated from fungi and mold, which are found in improperly manufactured and stored feed, while ensuring the safety of these fish meat for the consumer. Therefore, the organic properties of chitosan powder were examined in order to determine its impact on maturation of young <italic>Cyprinus carpio</italic>. Chitosan was tested in three samples of feedings at three concentrations: CH1 7gm/1kg fish feed, CH2 10gm/1kg, and CH3 15gm/1kg carp fish feed. The results showed that the third parameter, 15gm CH3 chitosan/kg of feed, was superior to the other parameters, having a highl</p> ... Show More
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Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
An Adaptive Digital Neural Network-Like-PID Control Law Design for Fuel Cell System Based on FPGA Technique
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This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH2) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Forward-Reverse Osmosis Processes for Oily Wastewater Treatment
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In this study, the feasibility of Forward–Reverse osmosis processes was investigated for treating the oily wastewater. The first stage was applied forward osmosis process to recover pure water from oily wastewater. Sodium chloride (NaCl) and magnesium chloride (MgCl2) salts were used as draw solutions and the membrane that was used in forward osmosis (FO) process was cellulose triacetate (CTA) membrane. The operating parameters studied were: draw solution concentrations (0.25 – 0.75 M), oil concentration in feed solution (FS) (100-1000 ppm), the temperature of FS and draw solution (DS) (30 - 45 °C), pH of FS (4-10) and the flow rate of both DS and FS (20 - 60 l/h). It was found that the water flux and oil concentration in FS increas

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Publication Date
Fri Jan 21 2022
Journal Name
Environmental Science And Pollution Research
Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams, United States
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Publication Date
Fri Dec 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Effect of speed and die holes diameter in the machine on feed pellets quality
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Abstract<p>The study aimed to effect of speed and die holes diameter in the machine on feed pellets quality. In this study was measured pellet direct measurement (%), pellet lengths (%), pellet durability (%) and pellet water absorption (%). Three die speeds 280, 300, and 320 rpm, three diameters of die holes in the machine 3, 4, and 5 mm, have been used. The results showed that increasing the pellet die speeds from 280 to 300 then to 320 rpm led to a significant decrease in direct measurement, pellet durability, and pellet water absorption was increased, whereas it did not significantly affect the pellet lengths. Increasing the die holes diameter from 3 to 4 then to 5 mm led to a significant de</p> ... Show More
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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Comparison study of Information Criteria to determine the order of Autoregressive models
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بهذا البحث نقارن معاييرالمعلومات التقليدية (AIC , SIC, HQ , FPE ) مع معيارمعلومات الانحراف المحور (MDIC) المستعملة لتحديد رتبة انموذج الانحدارالذاتي (AR) للعملية التي تولد البيانات,باستعمال المحاكاة وذلك بتوليد بيانات من عدة نماذج للأنحدارالذاتي,عندما خضوع حد الخطأ للتوزيع الطبيعي بقيم مختلفة لمعلماته

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Publication Date
Sun Sep 01 2024
Journal Name
Kufa Journal For Agricultural Sciences
Effect of feed forms, mash and pellets on productive performance and carcass weights of broiler chicken
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This study has aimed to investigate the effect of feed forms, mash and pellet on productive performance and carcass yields of broilers. 225 unsexed birds of the hybrid Ross 308 broiler were used, with a starting weight of 45.4 g one day old. The experiment lasted up to 35 days. The birds were randomly distributed into five treatments; each treatment contained 45 chicks according to three replicates (15 birds/ replicate). The experiment’s treatments included: (T1) Control mash 100% (pellet 0%), (T2) mash 75% (pellet 25%), (T3) mash 50% (pellet 50%), (T4) mash 25% (pellet 75%) and (T5) mash 0% (pellet 100%). Results were recorded a significant superior of T4 compared with other treatments (P≤0.05) in live body weight, weight gain,

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modified Grid Clustering Technique to Predict Heat Transfer Coefficient in a Duct of Arbitrary Cross Section Area
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A simple straightforward mathematical method has been developed to cluster grid nodes on a boundary segment of an arbitrary geometry that can be fitted by a relevant polynomial. The method of solution is accomplished in two steps. At the first step, the length of the boundary segment is evaluated by using the mean value theorem, then grids are clustered as desired, using relevant linear clustering functions. At the second step, as the coordinates cell nodes have been computed and the incremental distance between each two nodes has been evaluated, the original coordinate of each node is then computed utilizing the same fitted polynomial with the mean value theorem but reversibly.

The method is utilized to predict

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