## 3 Prototyping and Proposed Implementation  
### Designing Project Creation Simulator  
_Coestim_  
Optimizing an application's architecture starts by simulating the performance characteristics of that architecture using a software tool called a simulator. Simulators are essential elements in research because they have their main advantage the great flexibility in designing new architectures as well as in improving the existing architectures. After all, the time required for the development of a software simulator is much shorter. In addition, development costs are lower, and it is easier to resolve errors and problems. In the Coestim project, a series of models were made with the help of which we can build a hierarchical structure of a construction project. Each level of the hierarchy is defined as a service that has a list of materials used, a list of necessary resources, and a list of other services on which it depends to be executed, see Figure 4.  
Simulation algorithms for project creation have also been implemented. The project creation simulation algorithm is implemented in the following steps:  
1. Going through all the hierarchical structures of the super-services:  
- All parent super services are identified;  
Figure 4: Conceptual diagram of the database dedicated to the Coestim planner.  
For each super-parent service, the list of children is taken over;  
For each parent-child structure a random number is created between one and five projects with an initial number of estimates which is incremented at each iteration and values of service quantities, where the initial values are multiplied by the iteration number.  
Adding estimates to the project:  
Each super-service sequence is recursively traversed to create estimates in the same parent-child structure;  
The project-estimation link is created;  
For each estimate, the details specifying the items used in making it together with the prices and quantities thereof shall be added;  
For each estimate, add the resources used in its estimate.  
It was proposed to create, with the help of an artificial neural network, a design for the conceptual estimation of the length of a residential construction project. This proposed integrated model predicts the project completion time. Preliminary estimates of project parameters were based on the material estimate, which is the most vital information present for the potential project, as defined in the completed project database. The proposed artificial neural network system will be created in three phases. The three phases are vital in forming a precise ANN for predicting the time of a project. In addition, the quality and applicability of the data in the training database were considered the most fundamental elements to determine the accuracy of the forecast:  
1. **Modeling phase:** In this section, the ANN was modeled by defining the network architecture in which a series of parameters such as the number of layers, input parameters, and the number of neurons are defined. In addition, the amount of output data, the activation functions of the neuron, and the type of training function based on the network orientation were described.
2. **Training phase:** ANN training was based either on the training of this network structure or the weight of the training. In this section, the training algorithm was selected as supervised, unattended, or reinforcement training.
3. **Testing phase:** involves comparing the results of the proposed ANN model. This exercise is based on the data set for testing with the prospected values.  
The proposed methods for designing intelligent algorithms for activity planning were analyzed.