About
If you don’t have enough time to create a computational structure that utilizes multiple computational intelligence techniques (neural networks, fuzzy logic, optimization algorithms, etc.) simultaneously for your specific problem, you can entrust the modeling request to our team. On the Computational Intelligence website, researchers and scholars can refer their complex modeling problems and projects related to combined systems to our specialized team using the modeling request service. This service is designed for researchers seeking precise and intelligent modeling of complex problems using combined systems. Our team, leveraging outstanding experiences, will enable precise modeling of intricate issues. To place an order and use this service, you need to provide details and specifications of your problem through the pre-order form. After project feasibility assessment, a unique code will be sent to you. Then, you can proceed to finalize the order. Our goal is to provide optimal and tailored solutions to enhance your projects and research endeavors.
Important Points to Consider Before Ordering Modeling Services
Before placing an order, a feasibility check for creating an integrated model for the researcher’s specific problem needs to be conducted by our team. To initiate this process, please complete and submit the form below. After reviewing the problem’s conditions, a unique order registration code will be sent to you. The maximum time required for the review process is 7 working days.
Requirements for Presenting an Integrated Model
The description of the problem
A detailed and comprehensive explanation of the problem intended for modeling
The data and inputs
Information about the variables that will be used as inputs for modeling
The modeling objective:
Specify the precise goals you expect to achieve from the model
Model Parameters
Identify and describe the essential parameters that will influence the model's outcomes
Algorithms and Required Techniques
Explanation of the necessary algorithms and techniques for modeling and the rationale behind their selection
Timeline and Constraints
Setting the time for model execution along with specifying related constraints
Technical Details
Providing technical implementation details and specifics of the techniques for use in the model
Results and Interpretation
Introducing and interpreting the results obtained from the model and comparing them to the intended objectives
Evaluation and Model Correction
Methods and strategies for evaluating the accuracy and efficiency of the model and correcting it if necessary
Modeling Process
Explanation of the necessary process for training the model using the desired data
After the modeling, you will receive:
Final Model: The completed model based on the requested platform.
Figures and Tables: Relevant visuals and tables associated with the model, aiding in understanding the model’s structure and performance.
Detailed Numerical Information: In-depth numerical details of the model, including parameters, equations, and other relevant information.
Post-Delivery Revisions: The provision to request modifications or alterations to the initial model within a 7-day period after the delivery of the model.
