BROCHURE (VERSION 1.02.2021)
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MOBILE APP USER GUIDE
You can download civil mobile app user guide, here!
CIVIL WEB APPLICATION (VERSION 1.02.2021)
Access our app by tapping here and try it
WEB APP USER GUIDE
You can download civil web app user guide, here!
CIVIL APPLICATION (VERSION 1.02.2021)
You can download civil app for ios or android, here!
You can download it, here!
Civil web application demo
You can watch our product video, here!
Civil mobile application demo
You can watch our product video, here!
- Sign In(Log In Page)
- User’s Home page
- Access Management
- Training Models
- Model Variables
- Static Pages
- Economic Variables
- Construction Report
- File Manager
- Contact Us
Please Login into https://app.civilcostimator.com
Users who have previously registered for the Web Application must login by:
Entering their User Name.
Entering their Password.
Selecting Sign In to advance to the next screen and begin using the application.
Register a new membership Users who have not previously registered for the Web Application must select "Register a new membership" to access the "New User Registration" page.
If a user forgets his/her password, he/she must select “Forgotten password help.”
User will need to enter a valid email id which was entered at the time of
Registration and click on submit button to get notification about his/her Password
Check your mail and login again.
Users will be asked to enter or select the following information:
Name— First and Last
Enter the user’s first and last name.
Enter the user’s e-mail address. E-mail addresses are not case sensitive.
Passwords must be at least eight characters long and contain at least one letter character and one numeric character. Passwords are case sensitive.
I Agree to the Terms
Check the check-box to ensure that user accepts all Terms and Conditions.
The Admin Panel on the left side of the page includes following headers:
• Access Management
• Training Models
• Model Variables
• Static Page
• Economic Variables
• File Manager
Users: Where you can define the access level of each user. Also Edit ability is predicted there where you may define a range of date for each user’s password validity. In the meantime you may delete a user’s account.
Roles: An unlimited number of roles may be defined like: Admin, etc. Each user can have one or more roles.
Menu Permission: Where you define which parts of the menu are accessible for each role.
Considering that in this system, in general, 19 economic variables along with the financial information of the project have been used for forecasting, it is necessary for the system manager to determine for each educational model which of the economic variables he wants to use in the educational model. For example, in construction projects up to 9 floors, it may use all economic variables, but in a hospital project, it may use 15 variables as input to the educational model. It should be noted that the column number for each variable must be the same as the column number in the training Excel file.
Note: As mentioned, the names of the columns and their order in the Excel file containing the training data must be the same as the name and number of columns specified in the system.
So to work with this App, Push “Train Model”, Then “Select the file”, then “Start Training”. Once the situation of the model changes to “Trained” from “In Progress”;
This section is used by the end user of the system to predict the cost of construction. The 8 parameters is defined by the user with the following definitions and is used as input for the neural network along with the economic variables defined in the previous step:
1. Project locality defined in terms of zip codes
2. Total floor area of the building
3. Lot area
4. Total preliminary estimated construction cost based on the prices at the beginning of the project
5. Preliminary estimated construction cost based on the prices at the beginning of the project
6. Equivalent preliminary estimated construction cost based on the prices at the beginning of the project in a selected base year a
7. Duration of construction
8. Price of the unit at the beginning of the project per m2
After recording this information and storing, the status and cost predicted by the neural network will be visible.
It shows the season regarding which the dataset has been feed to the system. Normally 5 or more previous seasons should be feed.
Due to the fact that in this system 19 economic variables are used for training as input and the end user of the system should not be involved in entering this information when defining project information for forecasting, this access is given to the system administrator to provide economic information and enter each chapter in this section so that the end user can automatically extract economic variables and specify them as neural network input when specifying the year and start season of the system project.