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Artificial Neural Network Models to Predict the Cost and Time of Wastewater Projects
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Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was (26.24%), and (5.5%), and AA was (74%), and (94.5%), for cost and time model, respectively. The researcher concluded that the ANN model has a strong correlation and high accuracy, indicating that these models are characterized by high efficiency and good performance in predicting cost and time.

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Publication Date
Sat Apr 01 2023
Journal Name
Heliyon
A comprehensive review on modelling the adsorption process for heavy metal removal from waste water using artificial neural network technique
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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Robotics And Control (jrc)
Automated Stand-alone Surgical Safety Evaluation for Laparoscopic Cholecystectomy (LC) using Convolutional Neural Network and Constrained Local Models (CNN-CLM)
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In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Application Artificial Forecasting Techniques in Cost Management (review)
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For the duration of the last few many years many improvement in computer technology, software program programming and application production had been followed with the aid of diverse engineering disciplines. Those trends are on the whole focusing on synthetic intelligence strategies. Therefore, a number of definitions are supplied, which recognition at the concept of artificial intelligence from exclusive viewpoints. This paper shows current applications of artificial intelligence (AI) that facilitate cost management in civil engineering tasks. An evaluation of the artificial intelligence in its precise partial branches is supplied. These branches or strategies contributed to the creation of a sizable group of fashions s

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of The Mechanical Behavior Of Materials
Investigation of the performance of integrated intelligent models to predict the roughness of Ti6Al4V end-milled surface with uncoated cutting tool
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Abstract<p>Titanium alloys are broadly used in the medical and aerospace sectors. However, they are categorized within the hard-to-machine alloys ascribed to their higher chemical reactivity and lower thermal conductivity. This aim of this research was to study the impact of the dry-end-milling process with an uncoated tool on the produced surface roughness of Ti6Al4V alloy. This research aims to study the impact of the dry-end milling process with an uncoated tool on the produced surface roughness of Ti6Al4V alloy. Also, it seeks to develop a new hybrid neural model based on the training back propagation neural network (BPNN) with swarm optimization-gravitation search hybrid algorithms (PSO-GS</p> ... Show More
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Publication Date
Mon Sep 07 2020
Journal Name
Environmental Science And Pollution Research
The biosorption of reactive red dye onto orange peel waste: a study on the isotherm and kinetic processes and sensitivity analysis using the artificial neural network approach
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Publication Date
Sun Jun 01 2025
Journal Name
Methodsx
How mathematical models might predict desertification from global warming and dust pollutants
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Publication Date
Sat Aug 03 2024
Journal Name
Proceedings Of Ninth International Congress On Information And Communication Technology
Offline Signature Verification Based on Neural Network
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The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

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Publication Date
Fri Jun 01 2007
Journal Name
Al-khwarizmi Engineering Journal
Reduction of the error in the hardware neural network
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Specialized hardware implementations of Artificial Neural Networks (ANNs) can offer faster execution than general-purpose microprocessors by taking advantage of reusable modules, parallel processes and specialized computational components. Modern high-density Field Programmable Gate Arrays (FPGAs) offer the required flexibility and fast design-to-implementation time with the possibility of exploiting highly parallel computations like those required by ANNs in hardware. The bounded width of the data in FPGA ANNs will add an additional error to the result of the output. This paper derives the equations of the additional error value that generate from bounded width of the data and proposed a method to reduce the effect of the error to give

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Publication Date
Fri Nov 15 2024
Journal Name
Iraqi Journal Of Science
A Comparative Investigation of Different Ionospheric Models to Predict the MUF Parameter During Severe Geomagnetic Storm on 17th March 2015.
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The present work aimed to make a comparative investigation between three different ionospheric models: IRI-2020, ASAPS and VOACAP. The purpose of the comparative study is to investigate the compatibility of predicting the Maximum Usable Frequency parameter (MUF) over mid-latitude region during the severe geomagnetic storm on 17 March 2015. Three stations distributed in the mid-latitudes were selected for study; these are (Athens (23.50o E, 38.00o N), Jeju (124.53o E, 33.6o N) and Pt. Arguello (239.50o W, 34.80o N). The daily MUF outcomes were calculated using the tested models for the three adopted sites, for a span of five-day (the day of the event and two days preceding and following the event day). The calculated datasets were co

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Evaluation of the Current Status of the Cost Control Processes in Iraqi Construction Projects
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One of the most important problems of Iraqi construction projects is the cost variances, so it is important to identify the problems and shortcomings that cause poor cost control. Through the utilization of questionnaires, the study evaluated how project costs were managed and reported. The questionnaire was distributed to 180 professionals working in the Iraqi construction sector, with a response rate of 91%. The results showed that a high percentage of projects are implemented with a difference between real and estimated costs, and the process of documenting cost data needs to be more secure. On the other hand, there is a weakness in providing the necessary work structure information to monitor costs and a lack of proc

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