scholarly journals Estimation at Completion Simulation Using the Potential of Soft Computing Models: Case Study of Construction Engineering Projects

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 190 ◽  
Author(s):  
Enas Fathi Taher Al Hares ◽  
Cenk Budayan
Keyword(s):  
United Arab Emirates ◽  
Construction Projects ◽  
Harmony Search ◽  
Coupled Model ◽  
Forecast Model ◽  
Project Construction ◽  
Intelligence Models ◽  
Artificial Neural Network Ann ◽  
Learning Machine ◽  
High Level

“Estimation at completion” (EAC) is a manager's projection of a project's total cost at its completion. It is an important tool for monitoring a project's performance and risk. Executives usually make high-level decisions on a project, but they may have gaps in the technical knowledge which may cause errors in their decisions. In this current study, the authors implemented new coupled intelligence models, namely global harmony search (GHS) and brute force (BF) integrated with extreme learning machine (ELM) for modeling the project construction estimation at completion. GHS and BF were used to abstract the substantial influential attributes toward the EAC dependent variable, whereas the effectiveness of ELM as a novel predictive model for the investigated application was demonstrated. As a benchmark model, a classical artificial neural network (ANN) was developed to validate the new ELM model in terms of the prediction accuracy. The predictive models were applied using historical information related to construction projects gathered from the United Arab Emirates (UAE). The study investigated the application of the proposed coupled model in determining the EAC and calculated the tendency of a change in the forecast model monitor. The main goal of the investigated model was to produce a reliable trend of EAC estimates which can aid project managers in improving the effectiveness of project costs control. The results demonstrated a noticeable implementation of the GHS-ELM and BF-ELM over the classical and hybridized ANN models.

Sistema Híbrido Baseado Em Extreme Learning Machine E Harmony Search

2016 ◽  
Author(s):  
Edgar Wellington Marques de Almeida ◽  
Mêuser Jorge da Silva Valença
Keyword(s):  
Extreme Learning Machine ◽  
Harmony Search ◽  
Learning Machine

scholarly journals Application of an Artificial Neural Network to Automate the Measurement of Kinematic Characteristics of Punches in Boxing

2021 ◽  
Vol 11 (3) ◽  
pp. 1223
Author(s):  
Ilshat Khasanshin
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Kinematic Parameters ◽  
Constant Control ◽  
Measurement Units ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Effective Development ◽  
High Level ◽  
Different Levels

This work aimed to study the automation of measuring the speed of punches of boxers during shadow boxing using inertial measurement units (IMUs) based on an artificial neural network (ANN). In boxing, for the effective development of an athlete, constant control of the punch speed is required. However, even when using modern means of measuring kinematic parameters, it is necessary to record the circumstances under which the punch was performed: The type of punch (jab, cross, hook, or uppercut) and the type of activity (shadow boxing, single punch, or series of punches). Therefore, to eliminate errors and accelerate the process, that is, automate measurements, the use of an ANN in the form of a multilayer perceptron (MLP) is proposed. During the experiments, IMUs were installed on the boxers’ wrists. The input parameters of the ANN were the absolute acceleration and angular velocity. The experiment was conducted for three groups of boxers with different levels of training. The developed model showed a high level of punch recognition for all groups, and it can be concluded that the use of the ANN significantly accelerates the collection of data on the kinetic characteristics of boxers’ punches and allows this process to be automated.

scholarly journals Kajian Kompleksitas Proyek Konstruksi : Tinjauan Kegiatan Pengadaan Pekerjaan Konstruksi di Indonesia

2018 ◽  
Vol 13 (1) ◽  
pp. 35-45
Author(s):  
Cut Zukhrina Oktaviani
Keyword(s):  
Construction Projects ◽  
Construction Project ◽  
Government Procurement ◽  
External Factors ◽  
Construction Work ◽  
Project Construction ◽  
Internal And External Factors ◽  
And Control

This paper aims to reviewed construction projects complexity in construction complex procurement. Construction complexity is influenced with many internal and external factors. Complexity covers entire construction project cycles. At construction work procurement stage, organization and processes complexity is a major concern, especially in government procurement. Complexity requires regulation and control are such that it does not happen obstacles at every project construction cycle stage. 

scholarly journals PENENTUAN LOKASI TOWER CRANE PADA PROYEK KONSTRUKSI BERBASIS SIMULASI

2020 ◽  
Vol 3 (4) ◽  
pp. 1305
Author(s):  
Gerwyn Persulessy ◽  
Basuki Anondho
Keyword(s):  
Travel Time ◽  
Construction Projects ◽  
Tower Crane ◽  
Location Determination ◽  
Heavy Equipment ◽  
Total Travel Time ◽  
Speed Up ◽  
High Level ◽  
Map Data ◽  
Geometric Layout

Development of high-level building construction projects that require complex equipment that can be used in high-level construction, equipment used to help complete construction projects called heavy equipment. One of the heavy equipment used in high-rise buildings is a tower crane. The use and layout of tower cranes can speed up the schedule and save on project costs. Therefore many methods have been developed to determine the tower crane layout. This study will discuss determining the location of tower cranes by discussing simulations. The location will be determined based on the site map data which is processed in the form of a geometric arrangement and tower crane data specifications. Location determination is done by comparing the total travel time of several simulated locations according to several different speed criteria in a construction project. Speed criteria are divided into four times the jib speed and trolley speed. Location of the location with the total travel time will be taken as the final result. Different speed criteria will make the total travel time change. ABSTRAKPerkembangan proyek pembangunan gedung bertingkat tinggi yang semakin kompleks menyebabkan diperlukannya peralatan yang dapat mempermudah pembangunan gedung bertingkat, peralatan yang digunakan untuk membantu menyelesaikan tugas konstruksi disebut alat berat. Salah satu peralatan berat yang digunakan pada gedung bertingkat tinggi adalah tower crane. Penggunaan dan tata letak tower crane yang baik dapat mempercepat jadwal dan menghemat biaya proyek. Oleh karena itu banyak dikembangkan metode-metode untuk menentukan tata letak tower crane. Penelitian ini akan membahas penetapan letak lokasi tower crane dengan pendekatan  simulasi. Letak lokasi akan ditetapkan berdasarkan data site map yang diolah dalam bentuk geometric layout dan data spesifikasi tower crane. Penetapan lokasi dilakukan dengan cara membandingkan total travel time dari beberapa lokasi yang disimulasi sesuai dengan beberapa kriteria kecepatan yang berbeda-beda pada suatu proyek konstruksi. Kriteria kecepatan terbagi menjadi empat berdasarkan besarnya kecepatan jib dan kecepatan trolley. Letak lokasi dengan total travel time terkecil akan diambil sebagai hasil akhir. Kriteria-kriteria kecepatan yang berbeda disimulasi akan membuat total travel time berubah.

scholarly journals Identification and Qualitative Evaluation of Risk Factors in the Construction Projects in Iraq

2021 ◽  
Vol 14 (2) ◽  
pp. 91-101
Author(s):  
Noor Aletby ◽  
Hafeth Ibrahim
Keyword(s):  
Risk Factors ◽  
Risk Management ◽  
Construction Projects ◽  
Qualitative Evaluation ◽  
Qualitative Assessment ◽  
Management Process ◽  
Risk Management Process ◽  
Questionnaire Method ◽  
High Level ◽  
The Impact

Construction projects in Iraq face many dangers that cause exceeding the estimated cost of the project and not completing the project on time, and since the risk management process in construction projects is of great importance in controlling and reducing the impact of risks in construction projects, so it is necessary to identify these risks and evaluate them correctly in order to increase accuracy and the health of the subsequent stages of the risk management process in construction projects. This paper aims to identify the most important risks in construction projects in Iraq and to conduct a qualitative assessment of the identified risks and arrange them according to their importance. The researcher adopted the questionnaire method as a tool to determine the risks and used the technique of probability and effect matrix to conduct the qualitative assessment of the identified risks. The study found that there are 48 risk factors that constitute the most dangerous factor in construction projects in Iraq, and 10 of the determining factors were within the high level of risk, and at the forefront of which was the inability of the owner to finance the project.

scholarly journals Assessment of Artificial Intelligence Models for Estimating Lengths of Gradually Varied Flow Profiles

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Majid Niazkar ◽  
Farshad Hajizadeh mishi ◽  
Gökçen Eryılmaz Türkkan
Keyword(s):  
Artificial Intelligence ◽  
Water Surface ◽  
Direct Method ◽  
Step Method ◽  
Channel Networks ◽  
Intelligence Models ◽  
Artificial Intelligence Models ◽  
Surface Profiles ◽  
Artificial Neural Network Ann ◽  
Steep Slopes

The study of water surface profiles is beneficial to various applications in water resources management. In this study, two artificial intelligence (AI) models named the artificial neural network (ANN) and genetic programming (GP) were employed to estimate the length of six steady GVF profiles for the first time. The AI models were trained using a database consisting of 5154 dimensionless cases. A comparison was carried out to assess the performances of the AI techniques for estimating lengths of 330 GVF profiles in both mild and steep slopes in trapezoidal channels. The corresponding GVF lengths were also calculated by 1-step, 3-step, and 5-step direct step methods for comparison purposes. Based on six metrics used for the comparative analysis, GP and the ANN improve five out of six metrics computed by the 1-step direct step method for both mild and steep slopes. Moreover, GP enhanced GVF lengths estimated by the 3-step direct step method based on three out of six accuracy indices when the channel slope is higher and lower than the critical slope. Additionally, the performances of the AI techniques were also investigated depending on comparing the water depth of each case and the corresponding normal and critical grade lines. Furthermore, the results show that the more the number of subreaches considered in the direct method, the better the results will be achieved with the compensation of much more computational efforts. The achieved improvements can be used in further studies to improve modeling water surface profiles in channel networks and hydraulic structure designs.

scholarly journals FPGA Implementation of Weighted Online Sequential Extreme Learning Machine for Data Classification

2019 ◽  
Vol 9 (1) ◽  
pp. 6551-6557
Keyword(s):  
Extreme Learning Machine ◽  
High Speed ◽  
Bench Mark ◽  
Hardware Platform ◽  
Learning Speed ◽  
Field Programmable ◽  
Artificial Neural Network Ann ◽  
Learning Machine ◽  
Elm Classifier ◽  
Short Event

To design an efficient embedded module field-programmable gate array (FPGA) plays significant role. FPGA, a high speed reconfigurable hardware platform has been used in various field of research to produce the throughput efficiently. A now-a-days artificial neural network (ANN) is the most prevalent classifier for many analytical applications. In this paper, weighted online sequential extreme learning machine (WOS-ELM) classifier is presented and implemented in hardware environment to classify the different real-world bench-mark datasets. The faster learning speed, remarkable classification accuracy, lesser hardware resources, and short-event detection time, aid the hardware implementation of WOS-ELM classifier to design an embedded module. Finally, the developed hardware architecture of the WOS-ELM classifier is implemented on a high speed reconfigurable Xilinx Virtex (ML506) FPGA board to demonstrate the feasibility, effectiveness, and robustness of WOS-ELM classifier to classify the data in real-time environment.

scholarly journals An assessment of cost escalation in building construction project

2021 ◽  
Vol 39 (4) ◽  
pp. 1029-1034
Author(s):  
A. Nazif ◽  
A.K. Mustapha ◽  
F. Sani
Keyword(s):  
Construction Projects ◽  
Building Construction ◽  
Project Cost ◽  
Mean Values ◽  
Design Error ◽  
Project Construction ◽  
Effective Cost ◽  
Building Project ◽  
The Impact ◽  
The Relationship

Estimating of cost for building construction projects with minimum error at the conceptual stage of project development is quite  essential for planning. This study seeks to evaluate factors responsible for cost escalation of building construction projects.  Questionnaires were administered to examine and assess these factors. Subsequently, the mean score value of each factor was determined. In addition, Correlation and Linear regression analyses were used to establish the relationship between these factors. Factors responsible for cost escalation in projects were examined as well as the impact of those factors, and occurrence of those factors on project cost. The result of the analysis showed that, the most agreed factors responsible for project cost escalation were; inadequate supervision, irregular payment, and design error, having high mean values of 4.25, 4.20, and 4.15, respectively. Also, correlation analysis result established that the factors responsible for cost escalation and the impact of cost escalation had significant R and R2 of 0.81 and 0.70 respectively. Addressing these factors would go a long way in reducing the escalation of building project cost. Never the less, an effective cost management strategy is absolutely necessary to safeguard and sustain the construction  industry. Keywords: cost escalation, building project, construction, regression analysis

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