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Journal articles on the topic 'Complex and heterogeneous dynamic system'
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1
Naumkina, Dina, Alexander Rostovtsev, and Alexandr Abramov. "Digital heterogeneous dynamic model of peled Coregonus peled Gmelin." Fisheries 2020, no. 5 (October 9, 2020): 80–85. http://dx.doi.org/10.37663/0131-6184-2020-5-80-85.
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The article provides an example of constructing a complex dynamic model of a biological and economic system with the commodity two-year-old peled growing in Lake Ik in 2017-2018 as a case study. A brief description of the lake and a detailed description of the principle of constructing a heterogeneous dynamic model are given. A block diagram of a heterogeneous biological and economic system is under construction. The scenario of temporal development of the system is described. As a result, the model itself is presented in the form of graphs showing time dynamics of the amount of food, fish biomass, and working capital of the peled growing business process.
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Liu, Feng, and Yaguang Li. "Complex Nonlinear Dynamic System of Oligopolies Price Game with Heterogeneous Players Under Noise." International Journal of Bifurcation and Chaos 26, no. 11 (October 2016): 1650183. http://dx.doi.org/10.1142/s0218127416501832.
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A nonlinear four oligopolies price game with heterogeneous players, that are boundedly rational and adaptive, is built using two different special demand costs. Based on the theory of complex discrete dynamical system, the stability and the existing equilibrium point are investigated. The complex dynamic behavior is presented via bifurcation diagrams, the Lyapunov exponents to show equilibrium state, bifurcation and chaos with the variation in parameters. As disturbance is ubiquitous in economic systems, this paper focuses on the analysis of delay feedback control method under noise circumstances. Stable dynamics is confirmed to depend mainly on the low price adjustment speed, and if all four players have limited opportunities to stabilize the market, the new adaptive player facing profits of scale are found to be higher than the incumbents of bounded rational.
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Nilsson, Jacob, Saleha Javed, Kim Albertsson, Jerker Delsing, Marcus Liwicki, and Fredrik Sandin. "AI Concepts for System of Systems Dynamic Interoperability." Sensors 24, no. 9 (May 3, 2024): 2921. http://dx.doi.org/10.3390/s24092921.
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Interoperability is a central problem in digitization and sos engineering, which concerns the capacity of systems to exchange information and cooperate. The task to dynamically establish interoperability between heterogeneous cps at run-time is a challenging problem. Different aspects of the interoperability problem have been studied in fields such as sos, neural translation, and agent-based systems, but there are no unifying solutions beyond domain-specific standardization efforts. The problem is complicated by the uncertain and variable relations between physical processes and human-centric symbols, which result from, e.g., latent physical degrees of freedom, maintenance, re-configurations, and software updates. Therefore, we surveyed the literature for concepts and methods needed to automatically establish sos with purposeful cps communication, focusing on machine learning and connecting approaches that are not integrated in the present literature. Here, we summarize recent developments relevant to the dynamic interoperability problem, such as representation learning for ontology alignment and inference on heterogeneous linked data; neural networks for transcoding of text and code; concept learning-based reasoning; and emergent communication. We find that there has been a recent interest in deep learning approaches to establishing communication under different assumptions about the environment, language, and nature of the communicating entities. Furthermore, we present examples of architectures and discuss open problems associated with ai-enabled solutions in relation to sos interoperability requirements. Although these developments open new avenues for research, there are still no examples that bridge the concepts necessary to establish dynamic interoperability in complex sos, and realistic testbeds are needed.
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LIU, HUI-MIN, PATRICK WANG, HONG-QIANG WANG, and XIANG LI. "DYNAMIC MANAGEMENT OF MULTIPLE CLASSIFIERS IN COMPLEX RECOGNITION SYSTEM." International Journal of Pattern Recognition and Artificial Intelligence 26, no. 04 (June 2012): 1250006. http://dx.doi.org/10.1142/s0218001412500061.
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There are different kinds of multiple classifiers in complex recognition systems in pursuit of better recognition capabilities. To exploit the classifiers' potential as individual ones sufficiently and enable them to work cooperatively for the best classification results, they need to be considered as a whole and be dynamically managed according to the changing recognition occasions. In this paper, we present the conception of distributed Multiple Classifiers Management (MCM) and a self-adaptive recursive MCM model based on Mixture-of-Experts (ME). A control subsystem is consisted in the model, which allows the classification progress to be controlled by the systems' priori information when necessary. The model adjusts its parameters dynamically according to the current recognition state and gives the recognition results by combining the current individual classifiers' results with the previous combination result under priori information's control. An algorithm based on one step error correction is presented to acquire the model's parameters dynamically. It takes the previous times' ensemble classification results as true and corrects the current weights of the classifiers. At last, an experiment on the recognition of space objects is simulated. The experiment results show that the MCM model in this paper is effective for complex recognition system containing heterogeneous classifiers on improving the recognition rate and robustness.
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Wang, Jian, Xiaolin Qin, and Hongying Fang. "Virus-Information Coevolution Spreading Dynamics on Multiplex Networks." Complexity 2021 (March 5, 2021): 1–9. http://dx.doi.org/10.1155/2021/6624612.
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Virus and information spreading dynamics widely exist in complex systems. However, systematic study still lacks for the interacting spreading dynamics between the two types of dynamics. This paper proposes a mathematical model on multiplex networks, which considers the heterogeneous susceptibility and infectivity in two subnetworks. By using a heterogeneous mean-field theory, we studied the dynamic process and outbreak threshold of the system. Through extensive numerical simulations on artificial networks, we find that the virus’s spreading dynamics can be suppressed by increasing the information spreading probability, decreasing the protection power, or decreasing the susceptibility and infectivity.
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Yalamova, Rossitsa. "Financial Engineering in Complex Dynamic Systems." Financial Engineering 1 (November 28, 2023): 345–52. http://dx.doi.org/10.37394/232032.2023.1.32.
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This paper explores the dynamic nature of financial markets through the lens of complex adaptive systems (CAS) theory, aiming to provide a comprehensive understanding of how financial markets deviate from the Efficient Market Hypothesis in extreme events such as bubbles and crashes. Traditional economic models often struggle to capture the intricate dynamics of 'self-organizing' financial markets, particularly the interaction between supply and demand in the face of evolving risks. CAS theory offers a promising framework for modeling asset prices, emphasizing the interconnectedness and adaptability of various agents within the system. The literature review highlights the significance of CAS theory in understanding the collective adaptation that emerges from interactions among heterogeneous agents. Notably, researchers such as Holland (1995) and Axelrod (1997) have demonstrated how simple agent-level rules can lead to sophisticated, self-organizing behaviors at the system level, resulting in more efficient outcomes. This paper also discusses the pivotal role of financial engineering in enhancing the adaptive capacity of socioeconomic systems under extreme stress. In an increasingly unpredictable world characterized by natural disasters, economic crises, and other unforeseen events, risk management serves as a vital mechanism for volatility mitigation and financial protection. By spreading risk collectively through hedging strategies, financial engineering not only provides portfolio security but also contributes to the resilience of financial and economic systems. By merging insights from CAS theory and the role of financial engineering in increasing adaptive capacity, this paper contributes to a more comprehensive understanding of the risk dynamics in financial markets impacting economic activities. Financial engineering tools mitigate negative shocks and reduce the severity of recessionary cycles. An attempt is made to explain how collective adaptation can lead to more efficient risk management and pricing, ultimately helping policymakers, fund managers, and researchers navigate the complexities of modern financial markets and fortify socioeconomic systems against extreme stressors.
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Li, Zhi Hua, Hong Guang Yang, Jun Yu, and You Ping Gong. "Modeling and Simulation of the PMSM-Precision Reducer System with Modelica." Applied Mechanics and Materials 201-202 (October 2012): 202–7. http://dx.doi.org/10.4028/www.scientific.net/amm.201-202.202.
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There is still lack of effective modeling and simulation method for complex electromechanical coupling system. Modelica is a multi-domain unified modeling language to solve the modeling and simulation problems of the complex and heterogeneous physical systems. Dymola is a Modelica-based modeling and simulation platform for the complex physical systems. In this paper, the dynamics model of the permanent magnet synchronous motor (PMSM)-precision reducer system is established using Lagrange-Maxwell equation. The simulation model of this system is set up with Modelica language. The simulation of the system is realized in Dymola. Results show that the system can respond to good static and dynamic characteristics under a given speed for different loads. The dynamics model of the PMSM-precision reducer system can be further used in system control and optimization. The proposed modeling and simulation method based on Modelica may be commonly applied to other complex electromechanical systems.
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Zhao, Liuwei. "Dynamic Analysis and Chaos Control of Bertrand Triopoly Based on Differentiated Products and Heterogeneous Expectations." Discrete Dynamics in Nature and Society 2020 (July 11, 2020): 1–17. http://dx.doi.org/10.1155/2020/2012680.
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Price competition has become a universal commercial phenomenon nowadays. This paper considers a dynamic Bertrand price game model, in which enterprises have heterogeneous expectations. By the stability theory of the dynamic behavior of the Bertrand price game model, the instability of the boundary equilibrium point and the stability condition of the internal equilibrium point are obtained. Furthermore, bifurcation diagram, basin of attraction, and critical curve are introduced to investigate the dynamic behavior of this game. Numerical analysis shows that the change of model parameters in a dynamic system has a significant impact on the stability of the system and can even lead to complex dynamic behaviors in the evolution of the entire economic system. This kind of complex dynamic behavior will cause certain damage to the stability of the whole economic system, causing the market to fall into a chaotic state, which is manifested as a kind of market disorder competition, which is very unfavorable to the stability of the economic system. Therefore, the chaotic behavior of the dynamical system is controlled by time-delay feedback control and the numerical analysis shows that the effective control of the dynamical system can be unstable behavior and the rapid recovery of the market can be stable and orderly.
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Hoshu, Ayaz Ahmed, Liuping Wang, Shahzeb Ansari, Abdul Sattar, and Manzoor Hyder Alias Bilal. "System Identification of Heterogeneous Multirotor Unmanned Aerial Vehicle." Drones 6, no. 10 (October 20, 2022): 309. http://dx.doi.org/10.3390/drones6100309.
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An energy efficient heterogeneous multirotor unmanned aerial system (UAS) is presented in this paper, wherein, the aerodynamical characteristics of both helicopter and quadrotor are obtained in a single multirotor design. It features the energy efficiency and endurance of a helicopter, while keeping the mechanical simplicity, control and maneuverability of a quadrotor; employing a single large central rotor to get majority of the lift and four small arm canted rotors for control. Developing the stable and robust control strategy requires the accurate model of system. Due to the added mechanical complexities of the new design including the existence of couplings and gyroscopics, the modelling through the dynamic equations of the multirotor would not be possible in providing accurate results. Therefore, precise system modelling is required for the development of stable and robust control strategy. This paper proposes a novel system identification method with the objective to experimentally estimation of the precise dynamic model of the heterogeneous multirotor. The approach comprises of the utilization of input excitation signals, frequency sampling filter and derivation of transfer functions through complex curve fitting method. To validate the accuracy of the obtained transfer functions, the experimentally auto-tuned PID controllers are implemented over the transfer functions. Custom designed fight controller is used to experimentally implement the proposed idea. Presented results demonstrate the efficacy of the proposed approach for heterogeneous multirotor UAS.
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Gabriel, Alice-Agnes, Thomas Ulrich, Mathilde Marchandon, James Biemiller, and John Rekoske. "3D Dynamic Rupture Modeling of the 6 February 2023, Kahramanmaraş, Turkey Mw 7.8 and 7.7 Earthquake Doublet Using Early Observations." Seismic Record 3, no. 4 (October 1, 2023): 342–56. http://dx.doi.org/10.1785/0320230028.
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Abstract The 2023 Turkey earthquake sequence involved unexpected ruptures across numerous fault segments. We present 3D dynamic rupture simulations to illuminate the complex dynamics of the earthquake doublet. Our models are constrained by observations available within days of the sequence and deliver timely, mechanically consistent explanations of the unforeseen rupture paths, diverse rupture speeds, multiple slip episodes, heterogeneous fault offsets, locally strong shaking, and fault system interactions. Our simulations link both earthquakes, matching geodetic and seismic observations and reconciling regional seismotectonics, rupture dynamics, and ground motions of a fault system represented by 10 curved dipping segments and embedded in a heterogeneous stress field. The Mw 7.8 earthquake features delayed backward branching from a steeply branching splay fault, not requiring supershear speeds. The asymmetrical dynamics of the distinct, bilateral Mw 7.7 earthquake are explained by heterogeneous fault strength, prestress orientation, fracture energy, and static stress changes from the previous earthquake. Our models explain the northward deviation of its eastern rupture and the minimal slip observed on the Sürgü fault. 3D dynamic rupture scenarios can elucidate unexpected observations shortly after major earthquakes, providing timely insights for data-driven analysis and hazard assessment toward a comprehensive, physically consistent understanding of the mechanics of multifault systems.
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Yang, Xin, Shigang Wen, Zhifeng Liu, Cai Li, and Chuangxia Huang. "Dynamic Properties of Foreign Exchange Complex Network." Mathematics 7, no. 9 (September 9, 2019): 832. http://dx.doi.org/10.3390/math7090832.
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The foreign exchange (FX) market, one of the important components of the financial market, is a typical complex system. In this paper, by resorting to the complex network method, we use the daily closing prices of 41 FX markets to build the dynamical networks and their minimum spanning tree (MST) maps by virtue of a moving window correlation coefficient. The properties of FX networks are characterized by the normalized tree length, node degree distributions, centrality measures and edge survival ratios. Empirical results show that: (i) the normalized tree length plays a role in identifying crises and is negatively correlated with the market return and volatility; (ii) 83% of FX networks follow power-law node degree distribution, which means that the FX market is a typical heterogeneous market, and a few hub nodes play key roles in the market; (iii) the highest centrality measures reveal that the USD, EUR and CNY are the three most powerful currencies in FX markets; and (iv) the edge survival ratio analysis implies that the FX structure is relatively stable.
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Ortega-Arroyo, Jaime, Andrew J. Bissette, Philipp Kukura, and Stephen P. Fletcher. "Visualization of the spontaneous emergence of a complex, dynamic, and autocatalytic system." Proceedings of the National Academy of Sciences 113, no. 40 (September 16, 2016): 11122–26. http://dx.doi.org/10.1073/pnas.1602363113.
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Autocatalytic chemical reactions are widely studied as models of biological processes and to better understand the origins of life on Earth. Minimal self-reproducing amphiphiles have been developed in this context and as an approach to de novo “bottom–up” synthetic protocells. How chemicals come together to produce living systems, however, remains poorly understood, despite much experimentation and speculation. Here, we use ultrasensitive label-free optical microscopy to visualize the spontaneous emergence of an autocatalytic system from an aqueous mixture of two chemicals. Quantitative, in situ nanoscale imaging reveals heterogeneous self-reproducing aggregates and enables the real-time visualization of the synthesis of new aggregates at the reactive interface. The aggregates and reactivity patterns observed vary together with differences in the respective environment. This work demonstrates how imaging of chemistry at the nanoscale can provide direct insight into the dynamic evolution of nonequilibrium systems across molecular to microscopic length scales.
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Ma, Xiaogang, Chunyu Bao, Niu Yu, and Jing Xie. "Leader Selection and Dynamics Analysis under Leader-Based Collective Bargaining for Buyers’ Alliance." International Journal of Bifurcation and Chaos 31, no. 10 (August 2021): 2150156. http://dx.doi.org/10.1142/s021812742150156x.
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This paper focuses on the leader selection from the leader-based collective bargaining system, where buyers form an alliance and designate one of them as the leader to bargain with the supplier for a lower wholesale price of their common component. We construct the dynamic bargaining system consisting of two heterogeneous buyers and one supplier to analyze the influence of the enterprise nature and bargaining power on the leader selection. It was proved that the buyer with stronger bargaining power should be the leader. However, we find that, when the buyers are heterogeneous, the result may be different. In order to explore which factor plays a more important role in the leader selection, we design two rounds of bargaining for comparison. The interesting results imply that whether the bargaining power will reverse the leader selection in the first round depends on its growth rate. The nonlinear dynamics theory is also introduced to analyze the complex behaviors in the dynamic bargaining system. We analyze the influence of adjustment speed on the dynamic bargaining system and obtain the conditions required to maintain system stability. Considering the significance of system stability, the delayed feedback control mechanism is adopted to drive chaos back to stability.
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Shah, Sayed-Chhattan. "Design of a Machine Learning-Based Intelligent Middleware Platform for a Heterogeneous Private Edge Cloud System." Sensors 21, no. 22 (November 19, 2021): 7701. http://dx.doi.org/10.3390/s21227701.
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Recent advances in mobile technologies have facilitated the development of a new class of smart city and fifth-generation (5G) network applications. These applications have diverse requirements, such as low latencies, high data rates, significant amounts of computing and storage resources, and access to sensors and actuators. A heterogeneous private edge cloud system was proposed to address the requirements of these applications. The proposed heterogeneous private edge cloud system is characterized by a complex and dynamic multilayer network and computing infrastructure. Efficient management and utilization of this infrastructure may increase data rates and reduce data latency, data privacy risks, and traffic to the core Internet network. A novel intelligent middleware platform is proposed in the current study to manage and utilize heterogeneous private edge cloud infrastructure efficiently. The proposed platform aims to provide computing, data collection, and data storage services to support emerging resource-intensive and non-resource-intensive smart city and 5G network applications. It aims to leverage regression analysis and reinforcement learning methods to solve the problem of efficiently allocating heterogeneous resources to application tasks. This platform adopts parallel transmission techniques, dynamic interface allocation techniques, and machine learning-based algorithms in a dynamic multilayer network infrastructure to improve network and application performance. Moreover, it uses container and device virtualization technologies to address problems related to heterogeneous hardware and execution environments.
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Wen, Xuyun, Rifeng Wang, Weiyan Yin, Weili Lin, Han Zhang, and Dinggang Shen. "Development of Dynamic Functional Architecture during Early Infancy." Cerebral Cortex 30, no. 11 (June 12, 2020): 5626–38. http://dx.doi.org/10.1093/cercor/bhaa128.
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Abstract Uncovering the moment-to-moment dynamics of functional connectivity (FC) in the human brain during early development is crucial for understanding emerging complex cognitive functions and behaviors. To this end, this paper leveraged a longitudinal resting-state functional magnetic resonance imaging dataset from 51 typically developing infants and, for the first time, thoroughly investigated how the temporal variability of the FC architecture develops at the “global” (entire brain), “mesoscale” (functional system), and “local” (brain region) levels in the first 2 years of age. Our results revealed that, in such a pivotal stage, 1) the whole-brain FC dynamic is linearly increased; 2) the high-order functional systems tend to display increased FC dynamics for both within- and between-network connections, while the primary systems show the opposite trajectories; and 3) many frontal regions have increasing FC dynamics despite large heterogeneity in developmental trajectories and velocities. All these findings indicate that the brain is gradually reconfigured toward a more flexible, dynamic, and adaptive system with globally increasing but locally heterogeneous trajectories in the first 2 postnatal years, explaining why infants have rapidly developing high-order cognitive functions and complex behaviors.
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Petreska, Irina, Ljupco Pejov, Trifce Sandev, Ljupco Kocarev, and Ralf Metzler. "Tuning of the Dielectric Relaxation and Complex Susceptibility in a System of Polar Molecules: A Generalised Model Based on Rotational Diffusion with Resetting." Fractal and Fractional 6, no. 2 (February 5, 2022): 88. http://dx.doi.org/10.3390/fractalfract6020088.
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The application of the fractional calculus in the mathematical modelling of relaxation processes in complex heterogeneous media has attracted a considerable amount of interest lately. The reason for this is the successful implementation of fractional stochastic and kinetic equations in the studies of non-Debye relaxation. In this work, we consider the rotational diffusion equation with a generalised memory kernel in the context of dielectric relaxation processes in a medium composed of polar molecules. We give an overview of existing models on non-exponential relaxation and introduce an exponential resetting dynamic in the corresponding process. The autocorrelation function and complex susceptibility are analysed in detail. We show that stochastic resetting leads to a saturation of the autocorrelation function to a constant value, in contrast to the case without resetting, for which it decays to zero. The behaviour of the autocorrelation function, as well as the complex susceptibility in the presence of resetting, confirms that the dielectric relaxation dynamics can be tuned by an appropriate choice of the resetting rate. The presented results are general and flexible, and they will be of interest for the theoretical description of non-trivial relaxation dynamics in heterogeneous systems composed of polar molecules.
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Mergny, Pierre, and Satya N. Majumdar. "Stability of large complex systems with heterogeneous relaxation dynamics." Journal of Statistical Mechanics: Theory and Experiment 2021, no. 12 (December 1, 2021): 123301. http://dx.doi.org/10.1088/1742-5468/ac3b47.
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Abstract We study the probability of stability of a large complex system of size N within the framework of a generalized May model, which assumes a linear dynamics of each population size n i (with respect to its equilibrium value): d n i d t = − a i n i − T ∑ j J i j n j . The a i > 0’s are the intrinsic decay rates, J ij is a real symmetric (N × N) Gaussian random matrix and T measures the strength of pairwise interaction between different species. Our goal is to study how inhomogeneities in the intrinsic damping rates a i affect the stability of this dynamical system. As the interaction strength T increases, the system undergoes a phase transition from a stable phase to an unstable phase at a critical value T = T c. We reinterpret the probability of stability in terms of the hitting time of the level b = 0 of an associated Dyson Brownian motion (DBM), starting at the initial position a i and evolving in ‘time’ T. In the large N → ∞ limit, using this DBM picture, we are able to completely characterize T c for arbitrary density μ(a) of the a i ’s. For a specific flat configuration a i = 1 + σ i − 1 N , we obtain an explicit parametric solution for the limiting (as N → ∞) spectral density for arbitrary T and σ. For finite but large N, we also compute the large deviation properties of the probability of stability on the stable side T < T c using a Coulomb gas representation.
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Escobido, M. G. O., and N. Hatano. "Critical slowing down in a dynamic duopoly." International Journal of Modern Physics: Conference Series 36 (January 2015): 1560012. http://dx.doi.org/10.1142/s2010194515600125.
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Anticipating critical transitions is very important in economic systems as it can mean survival or demise of firms under stressful competition. As such identifying indicators that can provide early warning to these transitions are very crucial. In other complex systems, critical slowing down has been shown to anticipate critical transitions. In this paper, we investigate the applicability of the concept in the heterogeneous quantity competition between two firms. We develop a dynamic model where the duopoly can adjust their production in a logistic process. We show that the resulting dynamics is formally equivalent to a competitive Lotka-Volterra system. We investigate the behavior of the dominant eigenvalues and identify conditions that critical slowing down can provide early warning to the critical transitions in the dynamic duopoly.
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Volnikov, Mikhail. "Models of dynamics of complex heterostructures under pulsed force effects." E3S Web of Conferences 431 (2023): 02018. http://dx.doi.org/10.1051/e3sconf/202343102018.
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Relevance is due to insufficient knowledge and development of models of dynamics of complex heterostructures. Modern mechatronic systems include hybrid components consisting of complex heterogeneous structures: mechanical, electrical, electronic, etc. Heterostructures function in extreme conditions due to kinematic, dynamic, temperature, vibration and other external factors and are exposed to external influences. To create a reliable system for protecting complex heterostructures, it is necessary to build appropriate mathematical models that allow you to adequately describe the processes occurring in complex heterostructures. The purpose of the work is to study and develop heterostructural models based on the equations of point dynamics, plate and multilayer structures under the action of force and impulse loads in the presence or absence of internal friction in heterostructures. Particular attention is paid to the study of models of heterostructures with dissipation, with many degrees of freedom under the action of impulse loads.
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Long, Jianjun, and Hui Huang. "A Dynamic Stackelberg–Cournot Duopoly Model with Heterogeneous Strategies through One-Way Spillovers." Discrete Dynamics in Nature and Society 2020 (October 16, 2020): 1–11. http://dx.doi.org/10.1155/2020/3251609.
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Many works studied on complex dynamics of Cournot or Stackelberg games, but few references discussed a dynamic game model combined with the Cournot game phase and Stackelberg game phase. Under the assumption that R&D spillovers only flow from the R&D leader to the R&D follower, a duopoly Stackelberg–Cournot game with heterogeneous expectations is considered in this paper. Two firms with different R&D capabilities determine their R&D investments sequentially in the Stackelberg R&D phase and make output decisions simultaneously in the Cournot production phase. R&D spillovers, R&D investments, and technological innovation efficiency are introduced in our model. We find that: (i) the boundary equilibrium of the dynamic Stackelberg–Cournot duopoly system, where two players adopt boundedly rational expectation and naïve expectation, respectively, is unstable if the Nash equilibrium of the system is strictly positive. (ii) The Nash equilibrium of the dynamic Stackelberg–Cournot duopoly system, where two players adopt boundedly rational expectation and naïve expectation, respectively, is locally asymptotically stable only if the model parameters meet certain conditions. Especially, results indicate that small value of R&D spillovers or big value of output adjustment speed may yield bifurcations or even chaos. Numerical simulations are performed to exhibit maximum Lyapunov exponents, bifurcation diagrams, strange attractors, and sensitive dependence on initial conditions to verify our findings. It is also shown that the chaotic behaviors can be controlled with the state variables feedback and parameter variation method.
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Xiao, Jianli. "The Complex Dynamics of Sharing Platform Competition Game." Discrete Dynamics in Nature and Society 2021 (December 22, 2021): 1–14. http://dx.doi.org/10.1155/2021/2022179.
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With the rapid development of Internet technologies and online sharing platforms, sharing economy has become a major trend in economy. The entry of sharing economy leads to profound impacts on incumbent industry. We build a dynamic sharing platform competition model with which agents are bounded rational, and consumer side is heterogeneous. Then, we present the fixed points and the stability conditions of the bifurcation of the dynamic model. We simulate the adjustment speed of sharing platform, sharing platform price, and costs of traditional firm effects on system stability, and we present stable area, bifurcation diagram, the largest Lyapunov exponent, and strange attractor of different parameters, and we give a feedback control method at last. Our main results are as follows: (1) when adjustment speed of sharing platform increases, the system becomes bifurcation, and finally, the system goes into a chaotic state; when the system is stable, price of traditional firm and fee decision of sharing platform are constant. (2) When price of sharing platform increases, sharing platform is more stable while traditional firm is more vulnerable. Suppose the system is in the stable state; when sharing platform price increases, traditional firm price increases, while sharing platform fees decreases. (3) When traditional firm cost is small, the system would be more stable. When the system is stable, with traditional firm cost increasing, traditional firm price increases quicker than sharing platform consumer fee, while sharing platform seller fee decreases. (4) Feedback control can alleviate the chaotic state of system. With feedback control parameter increases, the system becomes more stable.
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Jing Chen. "Unified Dynamic Simulation System for Multi-Energy Flows of Electricity, Heat, and Gas in Integrated Energy Systems." Journal of Electrical Systems 20, no. 3 (April 25, 2024): 4936–46. http://dx.doi.org/10.52783/jes.6118.
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Integrated energy systems (IES) coordinate heterogeneous energy flows of electricity, heat, and gas to meet diverse load demands and enhance energy efficiency, is a new generation of energy systems that promote sustainable energy development. Simulation systems are essential tools for the analysis, control, and optimization of IES. However, due to the strong coupling of heterogeneous energy flows in IES, existing simulation software often lacks integration, typically focusing on electricity or relying on separate simulations of different energy flows. To address these challenges, this paper proposes a unified simulation technology for electricity, heat, and gas. First, the thermodynamic dynamic simulation capabilities of MATLAB/Simulink are extended using the Thermolib toolbox to create a unified modeling and simulation environment for coupled multi-energy flows. On this foundation, the energy conversion relationships and operating mechanisms of key multi-energy coupling equipment are studied, and dynamic Simulink models of the critical energy devices within the system are developed. Finally, a comprehensive dynamic simulation model for the multi-energy flows of the IES is constructed by connecting energy device models through an energy flow bus. The simulation results demonstrate that this system can effectively simulate the characteristics of electricity, heat, and gas flows across multiple time scales and the complex operating conditions of various energy devices within the MATLAB environment. This approach simplifies the multi-energy flow simulation structure and improves data transmission efficiency for multi-energy flows.
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Bahari, Akbar. "Nonlinear Dynamic Motivation-oriented Taxonomy of L2 Strategies based on Complex Dynamics Systems Theory." Journal of Language and Literature 19, no. 1 (April 1, 2019): 9–29. http://dx.doi.org/10.24071/joll.v19i1.1805.
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The need for a revisited framework of strategies in keeping with the nonlinear dynamic nature of motivational factors in L2 teaching led to the introduction of a taxonomy of nonlinear dynamic motivation-based strategies (NDMSs). This psycho-socio-cultural template suggests discovering dynamic motivational factors at individual level and integrating them into multiple parallel groups within a learner group instead of creating them which is a traditionally established function of motivational strategies to impose superficial cohesion on a learner group without catering for chaotic, emergent and dynamic individual motivational factors. Given the heterogeneity, dynamicity, and nonlinearity of the motivational factors at individual level, the first implication of the study is that NDMSs have the potential to activate identified motivational factors toward an adaptive and autonomous L2 motivation state regardless of their homogeneity or heterogeneity. Secondly, NDMSs have the potential to enable teachers to recruit the learning energy (i.e. motivation) from every member of the group via a dynamic and nonlinear set of motivational strategies instead of imposing a preset set of motivational strategies to all members of the group to elicit/facilitate/encourage equal performance from a motivationally heterogeneous learner group under the pretext of generating a cohesive learner group. Keywords: L2 motivation, nonlinear dynamic motivation-based strategies (NDMSs), complex dynamics systems theory (CDST)
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Lafond, Claude F., and Alan R. Levander. "Fast and accurate dynamic raytracing in heterogeneous media." Bulletin of the Seismological Society of America 80, no. 5 (October 1, 1990): 1284–96. http://dx.doi.org/10.1785/bssa0800051284.
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Abstract We have developed a fast and accurate dynamic raytracing method for 2.5-D heterogeneous media based on the kinematic algorithm proposed by Langan et al. (1985). This algorithm divides the model into cells of constant slowness gradient, and the positions, directions, and travel times of the rays are expressed as polynomials of the travel path length, accurate to the second other in the gradient. This method is efficient because of the use of simple polynomials at each raytracing step. We derived similar polynomial expressions for the dynamic raytracing quantities by integrating the raytracing system and expanding the solutions to the second order in the gradient. This new algorithm efficiently computes the geometrical spreading, amplitude, and wavefront curvature on individual rays. The two-point raytracing problem is solved by the shooting method using the geometrical spreading. Paraxial corrections based on the wavefront curvature improve the accuracy of the travel time and amplitude at a given receiver. The computational results for two simple velocity models are compared with those obtained with the SEIS83 seismic modeling package (Cerveny and Psencik, 1984); this new method is accurate for both travel times and amplitudes while being significantly faster. We present a complex velocity model that shows that the algorithm allows for realistic models and easily computes rays in structures that pose difficulties for conventional methods. The method can be extended to raytracing in 3-D heterogeneous media and can be used as a support for a Gaussian beam algorithm. It is also suitable for computing the Green's function and imaging condition needed for prestack depth migration.
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Chen, Haitao, Haitao Zhao, Li Zhou, Jiao Zhang, Yan Liu, Xiaoqian Pan, Xingguang Liu, and Jibo Wei. "A Dueling Deep Recurrent Q -Network Framework for Dynamic Multichannel Access in Heterogeneous Wireless Networks." Wireless Communications and Mobile Computing 2022 (October 1, 2022): 1–14. http://dx.doi.org/10.1155/2022/9446418.
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This paper investigates a deep reinforcement learning algorithm based on dueling deep recurrent Q -network (Dueling DRQN) for dynamic multichannel access in heterogeneous wireless networks. Specifically, we consider the scenario that multiple heterogeneous users with different MAC protocols share multiple independent channels. The goal of the intelligent node is to learn a channel access strategy that achieves high throughput by making full use of the underutilized channels. Two key challenges for the intelligent node are (i) there is no prior knowledge of spectrum environment or the other nodes’ behaviors; (ii) the spectrum environment is partially observable, and the spectrum states have complex temporal dynamics. In order to overcome the aforementioned challenges, we first embed the long short-term memory layer (LSTM) into the deep Q -network (DQN) to aggregate historical observations and capture the underlying temporal feature in the heterogeneous networks. And second, we employ the dueling architecture to overcome the observability problem of dynamic environment in neural networks. Simulation results show that our approach can learn the optimal access policy in various heterogeneous networks and outperforms the state-of-the-art policies.
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MARCHAL, PAUL, MURALI JAYAPALA, SAMUEL XAVIER DE SOUZA, PENG YANG, FRANCKY CATTHOOR, and G. DECONINCK. "MATADOR: AN EXPLORATION ENVIRONMENT FOR SYSTEM-DESIGN." Journal of Circuits, Systems and Computers 11, no. 05 (October 2002): 503–35. http://dx.doi.org/10.1142/s0218126602000598.
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We present a modular platform simulation environment to estimate the energy consumption and performance of distributed systems in a Systems-on-Chip context. We use the simulation environment to support the development of our high-level design methodologies. More in particular, we steer and verify the development of a task-level data transfer and storage methodology, the development of a task-level scheduling methodology and the development of an instruction memory management methodology. All of these methodologies are focussed on reducing the overall energy consumption of the complex dynamic system on a heterogeneous platform architecture. Compared to research in the academic and industrial context, our contribution is to integrate in a scalable way existing energy and performance simulators of the components of a heterogeneous multiprocessor SoC. Also a novel instruction memory hierarchy is included. The simulation environment consists of multiple processing nodes connected to a distributed memory hierarchy. To reduce the energy consumption of the system, both the processing nodes as well as the memory architecture can be varied: the processing voltage of each node can be tuned and the memory hierarchy can be fully customized. The integration of dynamic real-time applications on this platform is simplified by the availability of a multi-processor RTOS. The use of the simulator to develop our high-level design methodologies is illustrated on real-life multimedia applications.
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Fang, Chao, Tianyi Zhang, Jingjing Huang, Hang Xu, Zhaoming Hu, Yihui Yang, Zhuwei Wang, Zequan Zhou, and Xiling Luo. "A DRL-Driven Intelligent Optimization Strategy for Resource Allocation in Cloud-Edge-End Cooperation Environments." Symmetry 14, no. 10 (October 12, 2022): 2120. http://dx.doi.org/10.3390/sym14102120.
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Complex dynamic services and heterogeneous network environments make the asymmetrical control a curial issue to handle on the Internet. With the advent of the Internet of Things (IoT) and the fifth generation (5G), the emerging network applications lead to the explosive growth of mobile traffic while bringing forward more challenging service requirements to future radio access networks. Therefore, how to effectively allocate limited heterogeneous network resources to improve content delivery for massive application services to ensure network quality of service (QoS) becomes particularly urgent in heterogeneous network environments. To cope with the explosive mobile traffic caused by emerging Internet services, this paper designs an intelligent optimization strategy based on deep reinforcement learning (DRL) for resource allocation in heterogeneous cloud-edge-end collaboration environments. Meanwhile, the asymmetrical control problem caused by complex dynamic services and heterogeneous network environments is discussed and overcome by distributed cooperation among cloud-edge-end nodes in the system. Specifically, the multi-layer heterogeneous resource allocation problem is formulated as a maximal traffic offloading model, where content caching and request aggregation mechanisms are utilized. A novel DRL policy is proposed to improve content distribution by making cache replacement and task scheduling for arriving content requests in accordance with the information about users’ history requests, in-network cache capacity, available link bandwidth and topology structure. The performance of our proposed solution and its similar counterparts are analyzed in different network conditions.
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Ghosh, Tarun Kumar, and Sanjoy Das. "Efficient Job Scheduling in Computational Grid Systems Using Wind Driven Optimization Technique." International Journal of Applied Metaheuristic Computing 9, no. 1 (January 2018): 49–59. http://dx.doi.org/10.4018/ijamc.2018010104.
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Computational Grid has been employed for solving complex and large computation-intensive problems with the help of geographically distributed, heterogeneous and dynamic resources. Job scheduling is a vital and challenging function of a computational Grid system. Job scheduler has to deal with many heterogeneous computational resources and to take decisions concerning the dynamic, efficient and effective execution of jobs. Optimization of the Grid performance is directly related with the efficiency of scheduling algorithm. To evaluate the efficiency of a scheduling algorithm, different parameters can be used, the most important of which are makespan and flowtime. In this paper, a very recent evolutionary heuristic algorithm known as Wind Driven Optimization (WDO) is used for efficiently allocating jobs to resources in a computational Grid system so that makespan and flowtime are minimized. In order to measure the efficacy of WDO, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are considered for comparison. This study proves that WDO produces best results.
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Borisov, Vadim V., Sergey P. Kurilin, and Victor S. Luferov. "Fuzzy relational cognitive temporal models for analyzing and state prediction of complex technical systems." Journal Of Applied Informatics 17, no. 1 (97) (January 30, 2022): 27–38. http://dx.doi.org/10.37791/2687-0649-2022-17-1-27-38.
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The effectiveness of fuzzy cognitive modeling methods for analyzing and predicting the state of complex technical systems (STS) is justified by the following reasons: significant interdependence, non-linear nature and incompleteness of information about the mutual influence of the analyzed parameters of the CTS; a variety of effects of internal and external factors on the CTS; complexity and cost of conducting experimental studies during the operation of these systems. The main limitations of fuzzy cognitive models for modeling STS dynamics are: the complexity of taking into account the mutual influence of parameters with their different time lags relative to each other; the need for their constant operational adjustment and training of component models for all parameters during the operation of the CTS. In this paper, Fuzzy Relational Cognitive Temporal Models (FRCTM) are developed. These models combine the advantages of various types of fuzzy cognitive models, and at the same time neutralize the main limitations of the analysis and prediction of the state of the CTS, which are inherent in the well- known fuzzy cognitive models. The paper also proposes models of system dynamics that take into account the specifics of the FRCTM. We have also developed an approach and implemented a method for calculating fuzzy dependencies in vector-matrix form for dynamic modeling of the CTS. The proposed method makes it possible to solve the problems of increasing the uncertainty of the results and the output of fuzzy values of the FRCTM concepts beyond the ranges of the base sets due to the execution of mass iterative computations. An example of modeling heterogeneous electromechanical systems based on FRCTM is given. The results obtained are the basis for solving a whole range of tasks of analysis, predictive evaluation, modeling of different scenarios of the functioning and development of heterogeneous electromechanical systems for various system factors, operating modes and external conditions.
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Wang, Rui. "A Goal-Oriented Active Service Model and its COE Algorithm for Migrating Workflow System." Key Engineering Materials 426-427 (January 2010): 343–47. http://dx.doi.org/10.4028/www.scientific.net/kem.426-427.343.
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Workflow management systems (WFMS) are complex distributed systems, which are geared for the orchestration of business processes across multiple organizations. In order to adapt to the heterogeneous, distributed and dynamic environment, we propose a goal-oriented active service model. The model is designed to support organizational coevolution for providing workflow services. This paper reviews the introduction and motivation for active service approach, discusses the technologies used in active service, which represents steps towards the end goal of building virtual service group and organizational coevolutionary(COE) algorithm.
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Li, Yong Zhi. "Research on the Design and Realization of Management Information System of Enterprise Risk Assessment." Advanced Materials Research 998-999 (July 2014): 1666–69. http://dx.doi.org/10.4028/www.scientific.net/amr.998-999.1666.
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The smooth operation of virtual enterprise to obtain the expected profits, they must avoid the risks successfully, and virtual enterprise risk management system is an important guarantee of risk aversion. In view of its characteristics of distribution, dynamic complexity, the virtual enterprise risk management system is developed based on Web and multi-agent technology. Not only to meet the Distributed and heterogeneous of virtual enterprise operating environment, reflect the Independence of partner, and the complex relationship between the partners, but also provide decision support for decision-maker, and the system has strong robustness and reliability.
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Perišić, Ana, Ines Perišić, and Branko Perišić. "Simulation-Based Engineering of Heterogeneous Collaborative Systems—A Novel Conceptual Framework." Sustainability 15, no. 11 (May 30, 2023): 8804. http://dx.doi.org/10.3390/su15118804.
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We discuss the collaboration support of loosely coupled Smart Systems through configurable hyper-frameworks. Based on the system-of-systems (SoS) paradigm, in this article, we propose the model of a novel extendible conceptual framework with domain-specific moderation support for model-based simulations and the engineering of complex heterogeneous systems. The domain knowledge meta-model and corresponding management enterprise architecture enable the creation of template-based specializations. The proposed SoS conceptual framework meta-model represents an initial framework prototype that supports modeling, simulation, analysis, and utilization of dynamic architecting of heterogeneous SoS configurations. A Smart-Habitat concept encapsulating Smart-Area, Smart-City, Smart-Lot, Smart-Building, and Smart-Unit abstractions illustrate the frameworks’ applicability. The proposed SoS conceptual framework represents the initial conceptual support for modeling, simulation, analysis, and dynamic architecting of heterogeneous SoS configurations. We plan to refine the component architecture meta-model, specify a language workbench with Domain-Specific Orchestration Language support, and verify the configuration-based simulation manifest creation. These actions lead to the framework’s next stage, an operational framework (OF) instance, as a transitional artifact to the aimed software framework (SwF) counterpart.
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Liang, Zhimeng, Chunyi Cui, Kun Meng, Yu Xin, Huafu Pei, and Benlong Wang. "An Analytical Method for the Longitudinal Vibration of a Large-Diameter Pipe Pile in Radially Heterogeneous Soil Based on Rayleigh–Love Rod Model." Mathematics 8, no. 9 (August 28, 2020): 1442. http://dx.doi.org/10.3390/math8091442.
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Based on the Rayleigh–Love rod model and Novak’s plane-strain theory, an analytical method for the longitudinal vibration of a large-diameter pipe pile in radially heterogeneous soil is proposed. Firstly, the governing equations of the pile-soil system are established by taking both the construction disturbance effect and transverse inertia effect into account. Secondly, the analytical solution of longitudinal dynamic impedance at the pile top can be achieved by using Laplace transform and complex stiffness transfer techniques. Thirdly, the present analytical solution for dynamic impedance can also be performed in contrast with the existing solution to examine the correctness of the analytical method in this work. Further, the effect of pile Poisson’s ratio, pile diameter ratio as well as soil disturbed degree on the dynamic impedance are investigated. The results demonstrate that the Rayleigh–Love rod is appropriate for simulating the vibration of a large-diameter pipe pile in heterogeneous soils.
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Montes-Martínez, Josue-Rafael, Hugo Jiménez-Hernández, Ana-Marcela Herrera-Navarro, Luis-Antonio Díaz-Jiménez, Jorge-Luis Perez-Ramos, and Julio-César Solano-Vargas. "Dynamic Queries through Augmented Reality for Intelligent Video Systems." Applied System Innovation 7, no. 1 (December 19, 2023): 1. http://dx.doi.org/10.3390/asi7010001.
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Artificial vision system applications have generated significant interest as they allow information to be obtained through one or several of the cameras that can be found in daily life in many places, such as parks, avenues, squares, houses, etc. When the aim is to obtain information from large areas, it can become complicated if it is necessary to track an object of interest, such as people or vehicles, due to the vision space that a single camera can cover; this opens the way to distributed zone monitoring systems made up of a set of cameras that aim to cover a larger area. Distributed zone monitoring systems add great versatility, becoming more complex in terms of the complexity of information analysis, communication, interoperability, and heterogeneity in the interpretation of information. In the literature, the development of distributed schemes has focused on representing data communication and sharing challenges. Currently, there are no specific criteria for information exchange and analysis in a distributed system; hence, different models and architectures have been proposed. In this work, the authors present a framework to provide homogeneity in a distributed monitoring system. The information is obtained from different cameras, where a global reference system is defined for generated trajectories, which are mapped independently of the model used to obtain the dynamics of the movement of people within the vision area of a distributed system, thus allowing for its use in works where there is a large amount of information from heterogeneous sources. Furthermore, we propose a novel similarity metric that allows for information queries from heterogeneous sources. Finally, to evaluate the proposed performance, the authors developed several distributed query applications in an augmented reality system based on realistic environments and historical data retrieval using a client–server model.
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Sivakumar, B., T. Harter, and H. Zhang. "Solute transport in a heterogeneous aquifer: a search for nonlinear deterministic dynamics." Nonlinear Processes in Geophysics 12, no. 2 (February 8, 2005): 211–18. http://dx.doi.org/10.5194/npg-12-211-2005.
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Abstract. The potential use of a nonlinear deterministic framework for understanding the dynamic nature of solute transport processes in subsurface formations is investigated. Time series of solute particle transport in a heterogeneous aquifer medium, simulated using an integrated probability/Markov chain (TP/MC) model, groundwater flow model, and particle transport model, are studied. The correlation dimension method, a popular nonlinear time series analysis technique, is used to identify nonlinear determinism. Sensitivity of the solute transport dynamics to the four hydrostratigraphic parameters involved in the TP/MC model: (1) number of facies; (2) volume proportions of facies; (3) mean lengths (and thereby anisotropy ratio of mean length) of facies; and (4) juxtapositional tendencies (i.e. degree of entropy) among the facies is also studied. The western San Joaquin Valley aquifer system in California is considered as a reference system. The results indicate, in general, the nonlinear deterministic nature of solute transport dynamics (dominantly governed by only a very few variables, on the order of 3), even though more complex behavior is possible under certain (extreme) hydrostratigraphic conditions. The sensitivity analysis reveals: (1) the importance of the hydrostratigraphic parameters (in particular, volume proportions of facies and mean lengths) in representing aquifer heterogeneity; and (2) the ability of the correlation dimension method in capturing the (extent of) complexity of the underlying dynamics. Verification and confirmation of the present results through use of other nonlinear deterministic techniques and assessment of their reliability for a wide range of solute transport scenarios are recommended.
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Liu, Jia, Guoliang Liu, Na Li, and Hongliang Xu. "Dynamics Analysis of Game and Chaotic Control in the Chinese Fixed Broadband Telecom Market." Discrete Dynamics in Nature and Society 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/275123.
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This paper considers a dynamic duopoly Cournot model based on nonlinear cost functions. The model with heterogeneous players and the spillover effect is applied to the Chinese fixed broadband telecom market. We have studied its dynamic game process. The existence and stability of the Nash equilibrium of the system have been discussed. Simulations are used to show the complex dynamical behaviors of the system. The results illustrate that altering the relevant parameters of system can affect the stability of the Nash equilibrium point and cause chaos to occur. With the use of the delay feedback control method, the chaotic behavior of the model has been stabilized at the Nash equilibrium point. The analysis and results will be of great importance for the Chinese fixed broadband telecom market.
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Schäfer, Franziska, Lukas Engel, Marlene Kuhn, and Heiner Otten. "Combining Use Case Methodology and Architecture Models: A Standardized Description Methodology for Complex Systems." Applied Mechanics and Materials 882 (July 2018): 24–35. http://dx.doi.org/10.4028/www.scientific.net/amm.882.24.
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The European and International energy policy targets energy efficiency improvement and CO2reduction. Therefore, renewables are key players within our future energy supply system. In order to ensure security of energy supply and to avoid load peaks, highly interconnected power grids, also known as smart grids, have to deal with irregularities of phenomena such as sunlight, wind, tides and intelligently control these dynamic changes. Such a smart grid is denoted as a complex system. That is characterized by a large quantity of heterogeneous actors, collaborating within a dynamic and highly interconnected network. This results in big challenges in the steps planning, realizing and expanding such a system. These steps need to be based on a standardized description process to cope with the aforementioned challenges. In this paper, we combine the Smart Grid Architecture Model (SGAM) with the Use Case Methodology for describing processes in complex systems. Our new UC-SGAM Methodology exploits the benefits of both approaches and can also be applied to the Reference Architecture Model Industry 4.0 (RAMI4.0). The developed methodology is examined on two overload scenarios of the smart grid. It strongly enhances comparability and simplifies the visualization of complex use cases.
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Vodyaho, Alexander Ivanovich, Nataly Alexandrovna Zhukova, Yulia Alexandrovna Shichkina, Fahem Anaam, and Saddam Abbas. "About One Approach to Using Dynamic Models to Build Digital Twins." Designs 6, no. 2 (March 1, 2022): 25. http://dx.doi.org/10.3390/designs6020025.
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The modern stage of technology development is characterized by the emergence of new paradigms for the construction of anthropogenic systems, such as cyber-physical systems, socio-cybernetic systems, etc. The task of data acquisition about the state of a multi-level system and managing the structure and behavior of a system consisting of many thousands of elements of different physical nature is a complex task. This article describes one of possible approaches to solving the problem of data acquisition and management of the structure of a large-scale heterogeneous system. The proposed approach is based on the idea of using dynamic digital twins, which are dynamic models of the observed system. This approach was used for the development of systems in various subject domains, in particular, in production management systems built on the Industry 4.0 principle, in the development of a technical support system for cable television networks and in the development of support systems for the construction of educational trajectories.
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Town, Raewyn M., Parthasarathi Chakraborty, and Herman P. van Leeuwen. "Dynamic DGT speciation analysis and applicability to natural heterogeneous complexes." Environmental Chemistry 6, no. 2 (2009): 170. http://dx.doi.org/10.1071/en08091.
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Environmental context. The environmental fate and bioavailability of metal ions in natural waters is determined by their thermodynamic stability and kinetic features, both of which are distributed and depend on the metal ion loading of the system. Diffusive gradients in thin film (DGT) is a dynamic technique for metal speciation analysis that measures a certain portion of these complexes as determined by its operational timescale. Reliable interpretation of data furnished by DGT necessitates characterisation of its features for the particular case of heterogeneous complexes. Abstract. Owing to their inherent heterogeneity, the thermodynamic stability of metal ion complexes with natural ligands is characterised by a distribution, and thus is a function of metal-to-ligand ratio. The kinetic features of such metal complexes are also distributed and can be probed by dynamic speciation techniques. The kinetic regime of the metal complex sample can be manipulated via the metal-to-ligand ratio, and the timescale over which kinetic parameters are actually in effect is defined by the window of the chosen technique. Here we detail the kinetic features of diffusive gradients in thin film (DGT), and show that the range of attainable measurement timescales (τ) is rather limited: variation of the gel layer thickness practically allows only one order of magnitude in τ to be scanned. The more effective use of DGT to probe the distribution of dynamic metal species in heterogeneous systems is via variation of the metal-to-ligand ratio in the sample solution. Compilation of the literature DGT data for natural waters shows that by assuming a Freundlich isotherm relationship, the degree of heterogeneity is reflected in the measured DGT concentration as a function of metal ion loading.
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Buehler, Jennifer. "Capabilities in Heterogeneous Multi-Robot Systems." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (September 20, 2021): 2380–81. http://dx.doi.org/10.1609/aaai.v26i1.8184.
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Groups of robots are often able to to accomplish missions that no single robot can achieve by themselves. Teamwork is a very important factor in complex, dynamic domains. In heterogeneous teams, robustness and flexibility are increased by the diversity of the robots, each contributing different capabilities. In such heterogeneous Multi-Robot Systems it is reasonable to explicitly take the robots' capabilities into account when determining which one is best suited for a task. In this paper I present a framework that formalizes robots' capabilities and provides a means to estimate their suitability for a task. In highly unpredictable domains, accurate predictions of the outcomes of a robot's actions are virtually impossible. Approximate models and algorithms are required which help to estimate the outcome with highest possible confidence. The proposed architecture can provide estimates of task solution qualities at three levels of confidence: the lowest level only taking the mere existence of capabilities into account, the middle level considering task-specific details with approximate parameters of the capabilities, and the highest confidence level considering more elaborate planning algorithms.
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Chen, Bi Yu, Jianzhong Lu, Onyx W. H. Wai, and Xiaoling Chen. "Development of dynamic three-dimensional coastal information system: a case study in Hong Kong." Journal of Hydroinformatics 14, no. 3 (February 2, 2012): 815–28. http://dx.doi.org/10.2166/hydro.2012.048.
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Coastal-related data are four-dimensional in nature, varying not only in location and water depth but also in time. The heterogeneous and dynamic nature of coastal-related data makes modeling and visualization of these data a challenging task. A new object-oriented spatiotemporal data model to represent dynamic three-dimensional coastal data is proposed in this study. In the proposed model, a set of abstract data types allowing suitable spatiotemporal operations is defined to manipulate complex coastal data. In addition, a logical data model is proposed for the design of a spatiotemporal database. The proposed object-oriented and logical data models are implemented in a real-world coastal information management system in Hong Kong. An elegant visualization framework for displaying the coastal data, based on the concept of a time–depth bar, is presented in the case study.
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Chiao, L. Y., and Q. Liu. "Dependence of sandpile avalanche frequency–size distribution on coverage extent and compactness of embedded toppling threshold heterogeneity: implications for the variation of Gutenberg–Richter <i>b</i> value." Nonlinear Processes in Geophysics 21, no. 6 (December 5, 2014): 1185–93. http://dx.doi.org/10.5194/npg-21-1185-2014.
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Abstract. The effects of the spatiotemporal evolution of failure threshold heterogeneity on the dynamics of fault criticality, and thus on regional seismogenesis, have attracted strong interest in the field of regional seismotectonics. The heterogeneity might be a manifestation of the macroscopic distribution and multiscale strength variation of asperities, the distinct regional stress level, and (microscopically) heterogeneous fault surface roughness or friction regimes. In this study, rather than attempting to mimic the complex microscale slipping physics on a fault surface, sandpile cellular automata were implemented with a straightforward toppling rule. The objective is to examine the influence of distinct configurations of the embedded heterogeneous toppling threshold field on the global system avalanche event statistics. The examination results revealed that increasing the coverage extent and decreasing the compactness of the heterogeneous failure threshold, rather than the magnitude, range of contrast, diversity, or the geometric configuration of the threshold heterogeneity, leads to a systematic increase in the scaling exponent of the avalanche event power law statistics, implying the importance of mutual interaction among toppling sites with distinct thresholds. For tectonic provinces with differing stress regimes evolving spatio temporally, it is postulated that the distinct extent and compactness of the heterogeneous failure threshold are critical factors that manifest in the reported dynamic variations of seismicity scaling.
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Braun, Urs, Axel Schäfer, Henrik Walter, Susanne Erk, Nina Romanczuk-Seiferth, Leila Haddad, Janina I. Schweiger, et al. "Dynamic reconfiguration of frontal brain networks during executive cognition in humans." Proceedings of the National Academy of Sciences 112, no. 37 (August 31, 2015): 11678–83. http://dx.doi.org/10.1073/pnas.1422487112.
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The brain is an inherently dynamic system, and executive cognition requires dynamically reconfiguring, highly evolving networks of brain regions that interact in complex and transient communication patterns. However, a precise characterization of these reconfiguration processes during cognitive function in humans remains elusive. Here, we use a series of techniques developed in the field of “dynamic network neuroscience” to investigate the dynamics of functional brain networks in 344 healthy subjects during a working-memory challenge (the “n-back” task). In contrast to a control condition, in which dynamic changes in cortical networks were spread evenly across systems, the effortful working-memory condition was characterized by a reconfiguration of frontoparietal and frontotemporal networks. This reconfiguration, which characterizes “network flexibility,” employs transient and heterogeneous connectivity between frontal systems, which we refer to as “integration.” Frontal integration predicted neuropsychological measures requiring working memory and executive cognition, suggesting that dynamic network reconfiguration between frontal systems supports those functions. Our results characterize dynamic reconfiguration of large-scale distributed neural circuits during executive cognition in humans and have implications for understanding impaired cognitive function in disorders affecting connectivity, such as schizophrenia or dementia.
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Peng, Quan, and Shan Wang. "MASA: Multi-Application Scheduling Algorithm for Heterogeneous Resource Platform." Electronics 12, no. 19 (September 27, 2023): 4056. http://dx.doi.org/10.3390/electronics12194056.
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Heterogeneous architecture-based systems-on-chip enable the development of flexible and powerful multifunctional RF systems. In complex and dynamic environments where applications arrive continuously and stochastically, real-time scheduling of multiple applications to appropriate processor resources is crucial for fully utilizing the heterogeneous SoC’s resource potential. However, heterogeneous resource-scheduling algorithms still face many problems in practical situations, including generalized abstraction of applications and heterogeneous resources, resource allocation, efficient scheduling of multiple applications in complex mission scenarios, and how to ensure the effectiveness combining with real-world applications of scheduling algorithms. Therefore, in this paper, we design the Multi-Application Scheduling Algorithm, named MASA, which is a two-phase scheduler architecture based on Deep Reinforcement Learning. The algorithm is made up of neural network scheduler-based task prioritization for dynamic encoding of applications and heuristic scheduler-based task mapping for solving the processor resource allocation problem. In order to achieve stable and fast training of the network scheduler based on the actor–critic strategy, we propose optimization methods for the training of MASA: reward dynamic alignment (RDA), earlier termination of the initial episodes, and asynchronous multi-agent training. The performance of the MASA is tested with classic directed acyclic graph and six real-world application datasets, respectively. Experimental results show that MASA outperforms other neural scheduling algorithms and heuristics, and ablation experiments illustrate how these training optimizations improve the network’s capacity.
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Courtois, Peggy, Rammile Ettelaie, and Jianshe Chen. "Numerical Studies of Transport Properties in Heterogeneous Food Systems." Applied Rheology 16, no. 5 (October 1, 2006): 275–86. http://dx.doi.org/10.1515/arh-2006-0020.
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Abstract The current computer simulation based study aims to elucidate the complex role that the state of aggregation and morphology of the food materials plays in determining their transport behaviour. Using Brownian dynamic simulations, applied to colloidal systems, we simulate the compression of two different dense layers of nanoparticles (with reversible and irreversible bonds), at interface, at three different compression rates. We determine the desired transport coefficient for these structures using a novel technique, originally proposed by Torquato and Kim (1990). This method allows us to consider complex structures in our study, for which calculations of effective transport coefficients using conventional methods, like finite elements and finite difference, would be relatively difficult. We first validate our algorithm by comparing its results with those of exact calculations, for different regular lattices. Our results are in excellent agreement with the theory. The variation in the transport coefficient of nano-particle monolayers during the compression, are also correlated with the build up of stress and changes in the structure of the films.
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Nelson and Williams. "Bounding of Flow and Transport Analysis in Heterogeneous Saturated Porous Media: A Minimum Energy Dissipation Principle for the Bounding and Scale-Up." Hydrology 6, no. 2 (April 25, 2019): 33. http://dx.doi.org/10.3390/hydrology6020033.
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We apply minimum kinetic energy principles from classic mechanics to heterogeneous porous media flow equations to derive and evaluate rotational flow components to determine bounding homogenous representations. Kelvin characterized irrotational motions in terms of energy dissipation and showed that minimum dynamic energy dissipation occurs if the motion is irrotational; i.e., a homogeneous flow system. For porous media flow, reductions in rotational flow represent heterogeneity reductions. At the limit, a homogeneous system, flow is irrotational. Using these principles, we can find a homogenous system that bounds a more complex heterogeneous system. We present mathematics for using the minimum energy principle to describe flow in heterogeneous porous media along with reduced special cases with the necessary bounding and associated scale-up equations. The first, simple derivation involves no boundary differences and gives results based on direct Kelvin-type minimum energy principles. It provides bounding criteria, but yields only a single ultimate scale-up. We present an extended derivation that considers differing boundaries, which may occur between scale-up elements. This approach enables a piecewise less heterogeneous representation to bound the more heterogeneous system. It provides scale-up flexibility for individual model elements with differing sizes, and shapes and supports a more accurate representation of material properties. We include a case study to illustrate bounding with a single direct scale-up. The case study demonstrates rigorous bounding and provides insight on using bounding flow to help understand heterogeneous systems. This work provides a theoretical basis for developing bounding models of flow systems. This provides a means to justify bounding conditions and results.
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Chen, Pi-Yun, Hsu-Yung Lin, Neng-Sheng Pai, and Jing-Bin Huang. "Construction of Edge Computing Platform Using 3D LiDAR and Camera Heterogeneous Sensing Fusion for Front Obstacle Recognition and Distance Measurement System." Processes 10, no. 9 (September 16, 2022): 1876. http://dx.doi.org/10.3390/pr10091876.
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This research aims to utilise heterogeneous sensor fusion using 3D Light Detection and Ranging (LiDAR) and cameras, combined with an object recognition system and a ranging system, to construct an edge computing platform such that a vehicle equipped with the platform can perform computations offline in real time. This work comprises two main sections: the first is heterogeneous fusion, and the second is obstacle recognition and ranging detection. To achieve heterogeneous sensor fusion, 3D–3D point matching was used to find rigid body transformation between two sensors and finally project the LiDAR 3D point cloud image onto the 2D image. For object recognition, YOLOv4-Tiny was used as the detection network. A lightweight network architecture and high computational speed could be effectively used on edge computing hardware with limited performance. Further, by drawing the bounding box, we could detect the point cloud within the bounding box to estimate the distance to the obstacle. For detecting distance, we conducted experiments in two ways: ‘minimum point in box’ and ‘median point in box’ and compared the results. With heterogeneous sensor fusion, object recognition and the ranging system, detecting the category and distance of obstacles ahead of the vehicle was possible in real time. Furthermore, integrating the edge computing platform architecture enabled moving the entire system offline, making it an independent system that returns results in real time. Finally, a dynamic test was conducted on a road. The experiment showed that the detection speed of YOLOv4-Tiny in the dynamic test was higher than 60 FPS, and the accuracy rate surpassed 70%. Furthermore, the distance detection error of the 3D LiDAR was less than 3 cm, which is sufficiently accurate to be applied to complex environments on roads.
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Rüther, Tom, Patrick Mößle, Markus Mühlbauer, Oliver Bohlen, and Michael A. Danzer. "Iterative Dynamic Programming—An Efficient Method for the Validation of Power Flow Control Strategies." Electricity 3, no. 4 (October 12, 2022): 542–62. http://dx.doi.org/10.3390/electricity3040027.
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The operation of electrical networks, microgrids, or heterogeneous battery systems, especially the dispatch of single units within the system, requires sophisticated power flow control strategies. If objectives such as efficiency are demanded for the operation of the energy system, typical control strategies lack the ability to verify the optimality of the operation. Dynamic programming is a widely used method for determining the global optima of trajectory problems. In the context of energy systems and power flow optimization, it is restricted to applications with a low number of states and decisions. The reason for this is the rapid growth of computational effort with increasing dimensionality of the state and decision space. The approach of iterative dynamic programming (iDP) makes dynamic programming applicable to the planning and benchmarking of complex power flow optimization problems. To illustrate this, a heterogeneous battery energy storage system is introduced for which the iDP optimizes the power split at the point of common coupling to minimize the total cumulative loss of energy. The method can be adopted for a broad range of energy systems such as microgrids, utility grids, or electric vehicles. The applicability is limited only by the computation time, which depends on the model complexity and the length of the time series. To verify the functionality of the iterative dynamic programming, its results are directly compared to those of the standard dynamic programming. The total computation time can be reduced by 98% in the tested scenario. As relevant use cases, static and dynamic methods of power sharing are validated and benchmarked. The iDP offers a novel and computationally efficient method for the design and validation of power flow control strategies.
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Shramko, A. P. "Formalized model and algorithm for managing complex interaction of heterogeneous transport." Journal of Physics: Conference Series 2061, no. 1 (October 1, 2021): 012118. http://dx.doi.org/10.1088/1742-6596/2061/1/012118.
Full textAbstract:
Abstract The problem of ensuring the reliability of heterogeneous transport systems is extremely multifaceted and covers all stages of development - from design to operation. To increase efficiency, there is a need to harmonize the processes taking place in heterogeneous systems within the framework of single transport communication. The lack of appropriate theoretical justification leads in practice to the emergence of insufficiently substantiated decisions, because of which subsequent efforts made to eliminate the discovered shortcomings are, as a rule, costly and ineffective. Assessment of the system of integrated regulation of the transport system, from the point of view of its sustainability, is an indispensable condition for its operational efficiency and reliability. The efficiency of transport processes assumes that the effective functioning of local transport systems is ensured by the level of interaction between participants in the transport process, modes of transport that create positive dynamics of transit freight turnover. The paper substantiates the need for complex interaction in the management of the regional transport system, considering the interaction of adjacent modes of transport in a single information space. The method describes in detail the solution of forecasting and coordination problems in maritime transport systems, harmonization of the interests of heterogeneous transport in solving forecasting and control problems.
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Zhu, Ziming, Yuanzhen Song, and Menglin Qin. "Research on Evolutionary Game of Engineering Community Members from the Perspective of Engineering Ethics." E3S Web of Conferences 194 (2020): 05003. http://dx.doi.org/10.1051/e3sconf/202019405003.
Full textAbstract:
Engineering ethics is a system of ethical principles applied to engineering, which plays the role of value guidance and criterion evaluation in engineering construction activities. Based on engineering ethics, writers review the Sanmenxia Reservoir Project, and use system dynamics to systematically study the evolutionary game of engineering community members, including government, enterprise, and people, involved in the engineering activities. The results show that the engineering community is a heterogeneous community with complex game behaviors, and the correct ethical choice is the key factor that promotes the evolution of the community members to cooperative dynamic equilibrium. Good management of ethical commitment, emphasis on professionalism and public services, strengthening risk alert and avoidance are effective ways for members of the engineering community to form a cooperative game, avoid tragedy of public resources, and ultimately ensure the orderly development of projects.