Complex system management and application of visualization techniques

Complex system management and application of visualization techniques

Description of the specific policy

Cyber simulations can be performed due to recent advancements in IT capabilities. It is similar to a platform. A range of mathematical factors along with variables can be used, and the implications of using these factors and variables can be understood. The purpose should be taking the initiative and simulate the effects that will be developed in case of specific scenarios. One of the major aspects of IT simulation is the modification of the policy to get more in-depth insights regarding the theoretical representations (Yamada, Takahashi & Terano, 2019). There is a need to understand the practical implications of the policy deeply. A range of factors that are often associated with policy and simulations can make us understand the portions of the policy. For instance, the case of SmartCity can be considered.

In a SmartCity, the supply of water would be available for a specific time period, and everyone is supposed to complete their work within the specified time. Thereafter, policy developers can understand the real implications of implementing such a framework. It would be possible to stop water wastage in the city. People would be more conscious of their actions. Moreover, it would be possible to develop and implement a well-rounded water management system. However, it is essential to consider the various components and thereafter, focus on utilizing the components to their maximum potential. However, creating a SmartCity is not always easy because policymakers are supposed to consider a range of factors. It might not be feasible to limit the timing of water supply because citizens might feel troubled (Nguyen, 2014). Issues among citizens might also occur. It would be feasible to fill small buckets or a large pool in case of emergencies. During occasions, problems might also arise if the water supply becomes limited. These are exceptional cases; however, these are also important cases for further consideration. .

Visualization technique to make the model accessible

The suggested model should be made accessible to everyone. Therefore, a visualization technique should be used to fulfilling the purpose. The accessibility of the model would depend on a range of factors. The factors are interdependent as well. The placement of proper systems should be considered, as well. It would best to use a 3D model design to make the model more accessible and simple to understand (Boeykens, Santana Quintero, & Neuckermans, 2008). The purpose would be displaying the necessary actions and making the model far more practical before implementation. The first step would be the creation of an engine and using it after including the mathematical values and variables in its place. Data representation is necessary, and policy developers are supposed to understand these factors. Again, the real implications of the model should be inferred. The modal methods, data nodes, and graphs should be used to unlock the mystery.

Moreover, it would be feasible to use a histogram. This visualization tool would show overall trends and modifications. The purpose of taking these actions is to create a well-managed and developed system. The impact of the project must be beneficial for all. Good visualization depends on three principles. These are simple design, standard design, and, most importantly, scalable design. Simple design mainly refers to using consistency and incorporation of detailed information. Searching capabilities for users must be enhanced as well. The techniques should be sophisticated too. Similarly, good visualization refers to a data structure which is more standardized and up to the mark. The purpose should be presenting data in a flawless manner. The presented information must be concrete and easier to grasp. Lastly, scalable design means the accommodation of data sources and data volumes. The purpose is to present a more accurate and effective design.

References

Boeykens, S., Santana Quintero, M., & Neuckermans, H. (2008). Improving architectural design analysis using 3D modeling and visualization techniques. In Digital Heritage: Proceedings of the 14th International Conference on Virtual Systems and Multimedia (pp. 67-73). Archeolingua; Hungary.

Nguyen, T. N. A. (2014). Dynamic Multilevel Modeling in the design of Decision Support Systems for rescue simulation: combining Agent-based and Mathematical approaches (Doctoral dissertation).

Yamada, T., Takahashi, H., & Terano, T. (2019). Debriefing Framework for Business Games Using Simulation Analysis. Evolutionary Computing and Artificial Intelligence: Essays Dedicated to Takao Terano on the Occasion of His Retirement, 999, 64.