Dynamic system classifier

Stochastic differential equations describe well many physical, biological and sociological systems, despite the simplification often made in their derivation. Here the usage of simple stochastic differential equations to characterize and classify complex dynamical systems is proposed within a Bayesian framework. To this end, we develop a dynamic system classifier (DSC). The DSC first abstracts training data of a system in terms of time dependent coefficients of the descriptive stochastic differential equation. Thereby the DSC identifies unique correlation structures within the training data. For definiteness we restrict the presentation of DSC to oscillation processes with a time dependent frequency {\omega}(t) and damping factor {\gamma}(t). Although real systems might be more complex, this simple oscillator captures many characteristic features. The {\omega} and {\gamma} timelines represent the abstract system characterization and permit the construction of efficient signal classifiers. Numerical experiments show that such classifiers perform well even in the low signal-to-noise regime.Comment: 11 pages, 8 figure

Dynamic Ecological System Analysis

This article develops a new mathematical method for holistic analysis of nonlinear dynamic compartmental systems through the system decomposition theory. The method is based on the novel dynamic system and subsystem partitioning methodologies through which compartmental systems are decomposed to the utmost level. The dynamic system and subsystem partitioning enable tracking the evolution of the initial stocks, environmental inputs, and intercompartmental system flows, as well as the associated storages derived from these stocks, inputs, and flows individually and separately within the system. Moreover, the transient and the dynamic direct, indirect, acyclic, cycling, and transfer (diact) flows and associated storages transmitted along a given flow path or from one compartment, directly or indirectly, to any other are analytically characterized, systematically classified, and mathematically formulated. Further, the article develops a dynamic technique based on the diact transactions for the quantitative classification of interspecific interactions and the determination of their strength within food webs. Major concepts and quantities of the current static network analyses are also extended to nonlinear dynamic settings and integrated with the proposed dynamic measures and indices within the proposed unifying mathematical framework. Therefore, the proposed methodology enables a holistic view and analysis of ecological systems. We consider that this methodology brings a novel complex system theory to the service of urgent and challenging environmental problems of the day and has the potential to lead the way to a more formalistic ecological science.Comment: 45 pages, 15 figures. arXiv admin note: substantial text overlap with arXiv:1811.11885, arXiv:1811.1042

Multi-agent system for dynamic manufacturing system optimization

This paper deals with the application of multi-agent system concept for optimization of dynamic uncertain process. These problems are known to have a computationally demanding objective function, which could turn to be infeasible when large problems are considered. Therefore, fast approximations to the objective function are required. This paper employs bundle of intelligent systems algorithms tied together in a multi-agent system. In order to demonstrate the system, a metal reheat furnace scheduling problem is adopted for highly demanded optimization problem. The proposed multi-agent approach has been evaluated for different settings of the reheat furnace scheduling problem. Particle Swarm Optimization, Genetic Algorithm with different classic and advanced versions: GA with chromosome differentiation, Age GA, and Sexual GA, and finally a Mimetic GA, which is based on combining the GA as a global optimizer and the PSO as a local optimizer. Experimentation has been performed to validate the multi-agent system on the reheat furnace scheduling problem

Dynamic testing of docking system hardware

Extensive dynamic testing was conducted to verify the flight readiness of the Apollo docking hardware. Testing was performed on a unique six degree-of-freedom motion simulator controlled by a computer that calculated the associated spacecraft motions. The test system and the results obtained by subjecting flight-type docking hardware to actual impact loads and resultant spacecraft dynamics are described

Dynamic System Adaptation by Constraint Orchestration

For Paradigm models, evolution is just-in-time specified coordination conducted by a special reusable component McPal. Evolution can be treated consistently and on-the-fly through Paradigm's constraint orchestration, also for originally unforeseen evolution. UML-like diagrams visually supplement such migration, as is illustrated for the case of a critical section solution evolving into a pipeline architecture.Comment: 19 page

Dynamic gas temperature measurement system

The development of an advanced measuring system which measures the rapidly varying gas temperature at the exit of an aircraft jet engine combustor during ground based testing of hot section components was identified. Sensor guidelines, technical approach/program schedule, and the accomplishments are reviewed. The environment of a present generation combustor is shown. The method uses two beadless junctions type-B thermocouples to measure heat transfer coefficient in situ. Heat conduction effects are shown by a finite element model of the thermocouple

The dynamic magnetic behaviors of the Blume-Capel Ising bilayer system

The dynamic magnetic behaviors of the spin-1 Blume-Capel Ising bilayer system (BCIS) are studied in an oscillating external magnetic field on a two-layer square lattice by utilizing the mean field theory based on Glauber-type stochastic dynamics (DMFT). The dynamic equations describing the time-dependencies of the average magnetizations are obtained with the Master equation. The dynamic phases in this system are found by solving these dynamic equations. The temperature dependence of the dynamic order parameters is examined to characterize the nature (continuous or discontinuous) of the phase transitions and to obtain the dynamic phase transition points (DPT). The dynamic phase diagrams are shown for ferromagnetic / ferromagnetic, antiferromagnetic / antiferromagnetic, antiferromagnetic / antiferromagnetic interactions in the plane of the reduced temperature versus magnetic field amplitude and they display dynamic tricritical and reentrant behavior as well as the dynamic triple point

A comparative study of immune system based genetic algorithms in dynamic environments

Copyright @ 2006 ACMDiversity and memory are two major mechanisms used in biology to keep the adaptability of organisms in the ever-changing environment in nature. These mechanisms can be integrated into genetic algorithms to enhance their performance for problem optimization in dynamic environments. This paper investigates several GAs inspired by the ideas of biological immune system and transformation schemes for dynamic optimization problems. An aligned transformation operator is proposed and combined to the immune system based genetic algorithm to deal with dynamic environments. Using a series of systematically constructed dynamic test problems, experiments are carried out to compare several immune system based genetic algorithms, including the proposed one, and two standard genetic algorithms enhanced with memory and random immigrants respectively. The experimental results validate the efficiency of the proposed aligned transformation and corresponding immune system based genetic algorithm in dynamic environments

Dynamic gas temperature measurement system

A gas temperature measurement system with compensated frequency response of 1 KHz and capability to operate in the exhaust of a gas turbine combustor was developed. Environmental guidelines for this measurement are presented, followed by a preliminary design of the selected measurement method. Transient thermal conduction effects were identified as important; a preliminary finite-element conduction model quantified the errors expected by neglecting conduction. A compensation method was developed to account for effects of conduction and convection. This method was verified in analog electrical simulations, and used to compensate dynamic temperature data from a laboratory combustor and a gas turbine engine. Detailed data compensations are presented. Analysis of error sources in the method were done to derive confidence levels for the compensated data