Information Transfer Among the Components in Multi-Dimensional Complex Dynamical Systems

In this paper, a rigorous formalism of information transfer within a multi-dimensional deterministic dynamic system is established for both continuous flows and discrete mappings. The underlying mechanism is derived from entropy change and transfer during the evolutions of multiple components. While this work is mainly focused on three-dimensional systems, the analysis of information transfer among state variables can be generalized to high-dimensional systems. Explicit formulas are given and verified in the classical Lorenz and Chua’s systems. The uncertainty of information transfer is quantified for all variables, with which a dynamic sensitivity analysis could be performed statistically as an additional benefit. The generalized formalisms can be applied to study dynamical behaviors as well as asymptotic dynamics of the system. The simulation results can help to reveal some underlying information for understanding the system better, which can be used for prediction and control in many diverse fields.

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Real-time prediction and control of three-dimensional unsteady separated flow fields using neural networks

10.2514/6.1994-532 ◽

1994 ◽

Cited By ~ 6

Author(s):

William Faller ◽

Scott Schreck ◽

Marvin Luttges

Keyword(s):

Neural Networks ◽

Real Time ◽

Three Dimensional ◽

Separated Flow ◽

Flow Fields ◽

Time Prediction ◽

Prediction And Control ◽

And Control ◽

Unsteady Separated Flow

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Neural network prediction and control of three-dimensional unsteady separated flowfields

Journal of Aircraft ◽

10.2514/3.46866 ◽

1995 ◽

Vol 32 (6) ◽

pp. 1213-1220 ◽

Cited By ~ 15

Author(s):

William E. Faller ◽

Scott J. Schreck ◽

Marvin W. Luttges

Keyword(s):

Neural Network ◽

Three Dimensional ◽

Neural Network Prediction ◽

Prediction And Control ◽

Network Prediction ◽

And Control

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Three-dimensional deformation of laser quenching forming and its prediction and control method

The Proceedings of Conference of Kansai Branch ◽

10.1299/jsmekansai.2019.94.105 ◽

2019 ◽

Vol 2019.94 (0) ◽

pp. 105

Author(s):

Hiromichi NISHIDA

Keyword(s):

Control Method ◽

Three Dimensional ◽

Laser Quenching ◽

Prediction And Control ◽

And Control

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Three Dimensional Assembly Tolerance Analysis of Gear Drivetrain

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.655-657.1656 ◽

2013 ◽

Vol 655-657 ◽

pp. 1656-1661

Author(s):

Xiao Long Li ◽

Gui Hua Li ◽

Jun Ying Wang ◽

Hui Wang

Keyword(s):

Three Dimensional ◽

Tolerance Analysis ◽

Assembly Tolerance ◽

Analysis Process ◽

Assembly Accuracy ◽

3D Assembly ◽

Prediction And Control ◽

And Control ◽

Assembly Error ◽

Assembly Analysis

Assembly accuracy has a crucial impact on the movement, load and fatigue of gear drivetrain. In this paper, a methodology on the accuracy prediction and control of complex drivetrain is presented. The proposed approach tries to simplify the assembly tolerance computation but grasping main assembly error factors in the assembly process of gear drivetrain. Jacobian -Torsor method is used in the analysis process, and results show a proper performance which indicates a potential opportunity for further deep and wide research on the 3D assembly analysis and simplification method.

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An insight into Case Management and Challenges in Veteran Suicide Prevention

International Journal of Humanities and Applied Social Science ◽

10.33642/ijhass.v5n9p2 ◽

2020 ◽

pp. 14-25

Author(s):

Tamara Green

Keyword(s):

Case Management ◽

Suicide Prevention ◽

Suicide Risk ◽

Digital Transformation ◽

Prevention Science ◽

Historical Records ◽

Military Members ◽

Prediction And Control ◽

And Control ◽

Insight Into

Much of the literature, policies, programs, and investment has been made on mental health, case management, and suicide prevention of veterans. The Australian “veteran community is facing a suicide epidemic for the reasons that are extremely complex and beyond the scope of those currently dealing with them.” (Menz, D: 2019). Only limited work has considered the digital transformation of loosely and manual-based historical records and no enablement of Artificial Intelligence (A.I) and machine learning to suicide risk prediction and control for serving military members and veterans to date. This paper presents issues and challenges in suicide prevention and management of veterans, from the standing of policymakers to stakeholders, campaigners of veteran suicide prevention, science and big data, and an opportunity for the digital transformation of case management.

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