Stochastic Interference Research Articles

On-line measurement of COD and nitrate in water against stochastic background interference based on ultraviolet–visible spectroscopy and physics-informed multi-task learning

Traditional ultraviolet–visible spectroscopic quantitative analytical methods face challenges in simultaneous and long-term accurate measurement of chemical oxygen demand (COD) and nitrate due to spectral overlap and the interference from stochastic background caused by turbidity and chromaticity in water. Addressing these limitations, a compact dual optical path spectrum detection sensor is introduced, and a novel ultraviolet–visible spectroscopic quantitative analysis model based on physics-informed multi-task learning (PI-MTL) is designed. Incorporating a physics-informed block, the PI-MTL model integrates pre-existing physical knowledge for enhanced feature extraction specific to each task. A multi-task loss wrapper strategy is also employed, facilitating comprehensive loss evaluation and adaptation to stochastic backgrounds. This novel approach significantly outperforms conventional models in COD and nitrate measurement under stochastic background interference, achieving impressive prediction R2 values of 0.941 for COD and 0.9575 for nitrate, while reducing root mean squared error (RMSE) by 60.89 % for COD and 77.3 % for nitrate in comparison to the conventional chemometric model partial least squares regression (PLSR), and by 30.59 % and 65.96 %, respectively, in comparison to a benchmark convolutional neural network (CNN) model. The promising results emphasize its potential as a spectroscopic instrument designed for online multi-parameter water quality monitoring against stochastic background interference, enabling long-term accurate measurement of COD and nitrate levels.

Multi-strategy cooperative scheduling for airport specialized vehicles based on digital twins

Efficient specialized vehicle cooperative scheduling is significant for airport operations, particularly during times of high traffic, which reduces the risk of flight delays and increases customer satisfaction. In this paper,we construct a multi-type vehicles collaborative scheduling model with the objectives of minimizing vehicle travel distance and vehicle waiting time. Additionally, a three-layer genetic algorithm is designed, and the crossover and mutation operations are enhanced to address the scheduling model. Due to the numerous uncertainties and stochastic interferences in airport operations, conventional scheduling methods unable to effectively address these challenges, this paper combines improved genetic algorithm, simulation algorithm, and digital twins technology, proposing a multi-strategy scheduling framework for specialized vehicles based on digital twins. The scheduling framework utilises digital twins to capture dynamic data from the airport and continuously adjusts the scheduling plan through the scheduling strategy to ensure robust scheduling for specialized vehicles. In the event of severe delays at the airport, fast and efficient re-scheduling can be achieved. Finally, the effectiveness of the proposed scheduling framework is validated using domestic flight data, and extensive experiments and analyses are conducted in different scenarios. This research contributes to addressing the optimization problem of cooperative scheduling for multi-type vehicles at airports.

Performance analysis of an underwater wireless optical communication link with Lommel beam

In order to mitigate the stochastic interference of underwater channels and improve the quality of underwater communication systems, it is essential to study the performance of the underwater wireless optical communication (UWOC) links utilizing vortex beams with unique attributes. In this paper, the analytical formulae for the bit error rate (BER) and the average capacity of the UWOC link with diffraction-free Lommel beam are derived under the Rytov theory. Simulation results demonstrate that the system with a long wavelength, a high system signal-to-noise ratio(SNR), a small asymmetric parameter and receiving aperture diameter achieves a high average capacity and a low BER. Furthermore, in the underwater channel with a larger kinetic energy dissipation rate per unit mass of fluid and inner scale, a smaller mean-squared temperature dissipation rate, temperature salinity contribution ratio and transmission distance, the performance of the communication link can be improved. Meanwhile, it is found that the performance of the link with carrier Lommel beam are less sensitive to the topological charge, the scaling factor of the beam and the turbulent outer scale. These findings provide theoretical support for the design and implementation of an UWOC link utilizing the Lommel beam.

Evolution analysis of low-carbon cooperation of service providers based on Moran process in cloud manufacturing.

Low-carbon cooperation among cloud manufacturing service providers is one way to achieve carbon peak and neutrality. Such cooperation is related to the benefits to service providers adopting low-carbon strategies and stochastic factors such as government low-carbon policies, providers' environmental awareness, and demanders' low-carbon preferences. Focusing on the evolutionary process of service providers' low-carbon strategy selection under uncertain factors, a stochastic evolutionary game model is constructed based on the Moran process, and the equilibrium conditions for low-carbon cooperation among providers are analyzed under benefit-dominated and stochastic factor-dominated situations. Through numerical simulation, the effects of the cloud platform's cost-sharing coefficient for low-carbon investment, matching growth rate, carbon trading price, and group size on providers' low-carbon strategy evolution are analyzed. The research results show that increasing the cloud platform's low-carbon cost-sharing, carbon trading price, and group size can promote low-carbon cooperation among service providers. With greater low-carbon investment costs and greater stochastic factor interference, the providers' enthusiasm for low-carbon cooperation decreases. This study fills the research gap in the low-carbon cooperation evolution of cloud manufacturing providers based on the stochastic evolutionary game and provides decision-making suggestions for governments and cloud platforms to encourage provider participation in low-carbon cooperation and for providers to adopt low-carbon strategies.

Stochastic dual epidemic hypothesis model with Ornstein-Uhlenbeck process: Analysis and numerical simulations with SARS-CoV-2 variants

As it is widely known, the spread of infectious diseases can result in significant socioeconomic consequences and pose a threat to public health. However, biologically plausible models that incorporate stochastic interference and dual epidemic hypotheses have received limited attention. This paper aims to bridge this gap by examining a stochastic dual epidemic hypothesis model that incorporates Ornstein-Uhlenbeck processes to perturb the nonlinear incidence rate. We provide a rigorous analysis of the model, first proving the existence and uniqueness of global solution. We also analyze sufficient conditions for the extinction or persistence of each disease. Additionally, we establish the existence of an ergodic stationary distribution and derive expressions for the normal distribution followed by the global solution around the endemic equilibrium. Finally, using several numerical experimental examples, we validate our theoretical results with the case of dual variants of SARS-CoV-2 that can simultaneously infect humans. This paper contributes to the understanding of stochastic dual epidemic hypotheses and provides a foundation for future research in this field.

Experimental study of cavitation noise characteristics in a centrifugal pump based on power spectral density and wavelet transform

Cavitation is a harmful flow pattern in hydraulic machinery that disrupts the normal energy exchange and damages the flow channel components. Therefore, studying cavitation in hydraulic machinery and exploring efficient monitoring methods are currently key research topics. This paper examines the characteristics of inlet and outlet noise from centrifugal pumps at different stages of cavitation development under multiple flow rates. The results indicate that: The inlet and outlet noise of a centrifugal pump mainly consists of discrete noise and broadband noise. Discrete noise is shaft passage frequency, blade passage frequency, and their lower harmonic frequencies. The energy is mainly concentrated in discrete noise. Cavitation has a significant impact on the noise at the inlet, where the power spectral density of discrete noise and broadband noise both sharply decrease as cavitation develops, while the noise at the outlet is largely stable. Through relative energy analysis, it has been found that the relative energy of the different layers of noise at the inlet and outlet changes a lot as cavitation happens. The obvious wavelet energy fluctuation layer of inlet noise is relatively wide, while the obvious wavelet energy fluctuation layer of outlet noise is relatively concentrated, especially in the frequency-containing layer. The wavelet time-frequency diagram indicates that the cavitation noise of centrifugal pumps exhibits temporal stability and is devoid of stochastic interference. It can be observed that the sudden change in sound field during centrifugal pump cavitation is a significant characteristic, and earlier detection of cavitation occurrence can be achieved by analyzing the power spectral density of noise at both inlet and outlet of the pump as well as monitoring relative energy changes in wavelet decomposition layers.

Adaptive real-time similar repetitive manual procedure prediction and robotic procedure generation for human-robot collaboration

Manual procedure recognition and prediction are essential for practical human-robot collaboration in industrial tasks, such as collaborative assembly. However, current research mostly focuses on diverse human motions, while the similar repetitive manual procedures that are prevalent in real production tasks are often overlooked. Furthermore, the dynamic uncertainty caused by human-robot interferences and the generalisation of individuals, scenarios, and multiple sensor deployments pose challenges for implementing manual procedure prediction and robotic procedure generation. To address these issues, this paper proposes a real-time, similar repetitive procedure-oriented human skeleton processing system that employs the human skeleton as a robust modality. It utilises an improved deep spatial-temporal graph convolutional network and a FIFO queue-based discriminator for real-time data processing, procedure prediction, and generation. The proposed method is validated on multiple datasets with tens of individuals engaged in a real dynamic and uncertain human-robot collaborative assembly cell and able to run on entry-level hardware. The results demonstrate competitive performance of handcraft feature-free, early prediction and generalisation on individual variance, environment background, camera position, lighting conditions, and stochastic interference in human-robot collaboration.

How to promote municipal household waste management by waste classification and recycling? A stochastic tripartite evolutionary game analysis

Municipal household waste management (MHWM) is crucial for urban governance and sustainable development. Currently, Chinese governments at all levels are making great effort to implement MHWM through waste classification and recycling (WCR). However, the major participants in WCR, such as urban residents, property management companies and government departments, may act in their self-interest and hinder the MHWM goals. Therefore, it has become an imperative initiative to promote MHWM by effectively coordinate their conflicts of interest. Considering that external factors with complexity and uncertainty may also affect participants' behaviors, we develop a stochastic tripartite evolutionary game to model behavioral interaction of the three participants. Then we derive theoretical results and simulate different scenarios to examine the effects of key factors on participants’ strategy evolution. The results show that stochastic interference, cost reduction and rules simplification contribute to WCR of MHWM, and reward and performance improvement benefits have different incentive effects. Moreover, credit-based punishment and disclosure of non-compliance are more effective than financial-based penalty. To promote MHWM, policymakers should not only simplify classification rules, lower participation cost and enhance credit-based punishment system, but also encourage anonymous report and apply well-designed financial-based incentive and penalty.

State-Estimation-Based Control Strategy Design for Connected Cruise Control With Delays

The research on connected and automated vehicles attracts much attention recently. In connected vehicle systems, connected cruise control (CCC) is a wildly concerned technique to improve traffic safety and mitigate congestion. In this article, an optimal state-estimation-based (SE-based) control algorithm is proposed in a backward recursion manner to regulate CCC vehicle's longitudinal motion under stochastic communication delays, state noises, and channel interferences. Based on the analysis of error dynamics of vehicles and optimal state estimation strategy, the SE-based system dynamics is first formulated by using the Kalman filtering method. Then, a two-step SE-based control algorithm aiming at minimizing the quadratic system cost is proposed to enhance the vehicular platoon stability. In particular, the optimal control strategy can be generated online as a linear function of the estimated state information and previous control signals, and the corresponding coefficient can be iteratively calculated in an offline step. Finally, the results are successfully extended to the case of arbitrary communication delays, and the condition for the asymptotically mean square stability of the proposed optimal SE-based CCC algorithm is derived. Simulation results indicate that the proposed SE-based control algorithm has better system performance and control stability compared with existing works.

Adaptive event-triggered control for almost sure stability for vehicle platooning under interference and stochastic attacks

This paper considers the adaptive event-triggered strategy and controller design of vehicle platooning for stochastic attacks and interferences in communication channels. Bernoulli distribution and Markovian distribution Denial of Service models are introduced in this paper. In designing the controller, Aiming at the stochastic jamming attacks, the stability criterion is presented to guide the controller for almost sure string stability, and meanwhile aiming at the special safety requirements and the reduction of system interferences, the asymmetry event-triggered strategy framework is presented to adapt the transmission environment and the different safety requirements, which is designed to balance the principal concern in different situations. Finally, an example is introduced to demonstrate the controller performances of the vehicle platooning with the Bernoulli distribution and Markovian distribution DoS models, which implies that the presented methods are effective.

Dynamic behavior of a stochastic SIR model with nonlinear incidence and recovery rates

<abstract><p>The spread of infectious diseases are inevitably affected by natural and social factors, and their evolution presents oscillations and other uncertainties. Therefore, it is of practical significance to consider stochastic noise interference in the studies of infectious disease models. In this paper, a stochastic SIR model with nonlinear incidence and recovery rate is studied. First, a unique global positive solution for any initial value of the system is proved. Second, we provide the sufficient conditions for disease extinction or persistence, and the influence of threshold $ \tilde{R_{0}} $ of the stochastic SIR model on disease state transition is analyzed. Additionally, we prove that the system has a stationary distribution under some given parameter conditions by building an appropriate stochastic Lyapunov function as well as using the equivalent condition of the Hasminskii theorem. Finally, the correctness of these theoretical results are validated by numerical simulations.</p></abstract>

Dynamic behavior of stochastic predator-prey system

<abstract> <p>In this paper, a stochastic predator-prey system with mutual interference is studied, which provides guidance on creating appropriate biodegradable environments. By utilizing Mawhin's coincidence degree theorem and constructing a suitable Lyapunov function, a Volterra model with mutual interference is studied. A few sufficient conditions are obtained for existence, extinction and global asymptomatic stability of the positive solution of the model. Then we perform various numerical simulations to verify the stochastic and deterministic systems are global asymptotically stable. It is significant that such a model is firstly proposed with stochastic mutual interference.</p> </abstract>

DYNAMICS OF A STOCHASTIC VECTOR-HOST EPIDEMIC MODEL WITH AGE-DEPENDENT OF VACCINATION AND DISEASE RELAPSE

Due to the ubiquitous stochastic interference in nature, the uncertainty of the disease relapse and the duration of immunity, we present a stochastic vector-host epidemic model with age-dependent of vaccination and disease relapse, where two general incidences are also introduced to depict the transmission of virus between vectors and hosts. By constructing a suitable Lyapunov function, the existence and uniqueness of the global positive solution of our model are proved. Further, the stochastic extinction of disease, the existence of stationary distribution are also discussed. Moreover, the stochastic extinction of disease and the existence of stationary distribution for special incidence are obtained as an application, where the general incidence degenerates into the billinear incidence. Finally, numerical simulations are given to illuminate the main results, which also suggest that the behaviors of vectors and the self-protection of hosts are the key factors to eliminate the disease relative to the quantity of vector population during the transmission of vector-host infectious diseases.

Stochastic dynamic analysis of a chemostat model of intestinal microbes with migratory effect

<abstract><p>This paper proposes a stochastic intestinal chemostat model considering microbial migration, intraspecific competition and stochastic perturbation. First, the extinction and persistence in mean of the intestinal microbe of the chemostat model are investigated by constructing the appropriate Lyapunov functions. Second, we explore and obtain sufficient conditions for the existence and uniqueness of an ergodic stationary distribution of the model by using ergodic theory. The results show stochastic interference has a critical impact on the extinction and sustainable survival of the intestinal microbe. Eventually, numerical simulations are carried out to verify the theoretical results.</p></abstract>

IMT to Satellite Stochastic Interference Modeling and Coexistence Analysis of Upper 6 GHz-Band Service

IMT to Satellite Stochastic Interference Modeling and Coexistence Analysis of Upper 6 GHz-Band Service

ШИРОКОПОЛОСНЫЙ РЕФЛЕКТОМЕТРИЧЕСКИЙ МЕТОД ИЗМЕРЕНИЯ ВЛАЖНОСТИ И СТЕПЕНИ ШЕРОХОВАТОСТИ ПОВЕРХНОСТИ ПОЧВЫ

In this article, a numerical-analytical model of the reflection coefficient of an electromagnetic wave from a rough soil surface is proposed. Based on the created model of reflection coefficient, in the frequency range from 520 MHz to 1.26 GHz, a broadband method for the root-mean-square deviation (RMS) of heights and volumetric moisture of rough soil surface is developed. When the model of reflection coefficient creating, the field of reflected wave from the rough soil surface was presented as the sum of secondary fields from an infinite set of elementary horizontal scattering plates (with a given average size). The field from each elementary scattering plate is represented as an average field from the result of stochastic interference of an infinite set of coherent elementary sources of secondary waves. The vertical position of the elementary sources is determined by the stochastic height of the soil surface within elementary plate. It is shown that the created model describes the total value of reflection coefficient (coherent and diffuse components) with the determination coefficient of R2=0.981 and root-mean square error (RMSE) no more than 0.35 dB, relative to the reflection coefficient, calculated by the finite difference method and the advanced integral equations method. The possibility of RMS heights and volumetric moisture of rough soil surface retrieval, relative to the true values, was shown no worse than R2=0.909 (RMSE=0.4 cm) and R2=0.975 (RMSE=2%), respectively. This analysis was carried out on the example of 16 soil samples, the complex permittivity of which was measured for a wide range of dry bulk densities from 0.7 g/cm3 to 1.8 g/cm3, moisture content, texture with variation clay content from 0% to 76% and organic matter content from 0.6% to 6.9%. The results have a wide application value both for single-frequency and multi-frequency radar and radiometric methods of soil moisture measuring.

Dynamical behavior and optimal impulse control analysis of a stochastic rumor spreading model

The Internet era has brought great convenience to our life and communication. Meanwhile, it also makes a bunch of rumors propagate faster and causes even more harm to human life. Therefore, it is necessary to perform effective control mechanisms to minimize the negative social impact from rumors. Thereout, firstly, we formulate a rumor spreading model considering psychological factors and thinking time, then, we add white noise (i.e., stochastic interference) and two pulse control strategies which denote education mechanism and refutation mechanism into the model. Secondly, we obtain the global positive solutions and demonstrate the global exponential stability of the unique positive periodic rumor-free solution. Thirdly, we discuss the extinction and persistence of rumor. Moreover, we use Pontriagin’s minimum principle to explore the optimal impulse control. Finally, several numerical simulations are carried out to verify the effectiveness and availability of the theoretical analysis. We conclude that the pulse control strategies have a great influence on controlling rumor spreading, and different control strategies should be adopted under different transmission scenarios.

Dynamic Behavior of an Interactive Mosquito Model under Stochastic Interference

For decades, mosquito-borne diseases such as dengue fever and Zika have posed serious threats to human health. Diverse mosquito vector control strategies with different advantages have been proposed by the researchers to solve the problem. However, due to the extremely complex living environment of mosquitoes, environmental changes bring significant differences to the mortality of mosquitoes. This dynamic behavior requires stochastic differential equations to characterize the fate of mosquitoes, which has rarely been considered before. Therefore, in this article, we establish a stochastic interactive wild and sterile mosquito model by introducing the white noise to represent the interference of the environment on the survival of mosquitoes. After obtaining the existence and uniqueness of the global positive solution and the stochastically ultimate boundedness of the stochastic system, we study the dynamic behavior of the stochastic model by constructing a series of suitable Lyapunov functions. Our results show that appropriate stochastic environmental fluctuations can effectively inhibit the reproduction of wild mosquitoes. Numerical simulations are provided to numerically verify our conclusions: the intensity of the white noise has an effect on the extinction and persistence of both wild and sterile mosquitoes.

Replicator dynamics of the Hawk-Dove game with different stochastic noises in infinite populations

This paper investigates the dynamic system of the Hawk-Dove game with deterministic and stochastic interference and considers the two-player game and N-player game, respectively. First, we introduce the replicator dynamics equations of the Hawk-Dove game for the two-player and N-player cases and prove the stability of the unique equilibrium point. When the system reaches a stable state, we find that the frequency of individuals adopting D-strategy depends upon the number of players. As the number of players increases, the frequency of D-strategy increases. Second, we ponder two forms of stochastic noise, additive noise and multiplicative noise, and use the potential function method to prove the stochastic stability of equilibria of the two-player and N-player game systems respectively. The additive noise causes the frequency of players who use D-strategy to oscillate at the stochastically stable equilibrium. Then, we use Itô’s formula and the strong law of large numbers to prove that the frequency of D-strategy is almost surely exponentially stable (ASES) and persistent. We obtain a threshold value for multiplicative noise, when the multiplicative noise value is greater than the threshold value, the frequency of D-strategy x=0 is ASES. Conversely, when the multiplicative noise value is less than the threshold value, the frequency of D-strategy is persistent. The results show that noise interference has an important effect on the replicator dynamics of Hawk-Dove game, this improves the study of game dynamics without noise. Finally, numerical simulations are used to show our theoretical results.

The stochastic evolutionary game analysis of public prevention and control strategies in public health emergencies

PurposeThe COVID-19 epidemic is still spreading globally and will not be completely over in a short time. Wearing a mask is an effective means to combat the spread of COVID-19. However, whether the public wear a mask for epidemic prevention and control will be affected by stochastic factors such as vaccination, cultural differences and irrational emotions, which bring a high degree of uncertainty to the prevention and control of the epidemic. The purpose of this study is to explore and analyze the epidemic prevention and control strategies of the public in an uncertain environment.Design/methodology/approachBased on the stochastic evolutionary game model of the Moran process, the study discusses the epidemic prevention and control strategies of the public under the conditions of the dominance of stochastic factors, expected benefits and super-expected benefits.FindingsThe research shows that the strategic evolution of the public mainly depends on stochastic factors, cost-benefit and the number of the public. When the stochastic factors are dominant, the greater the perceived benefit, the lower the cost and the greater the penalty for not wearing masks, the public will choose to wear a mask. Under the dominance of expected benefits and super-expected benefits, when the number of the public is greater than a certain threshold, the mask-wearing strategy will become an evolutionary stable strategy. From the evolutionary process, the government’s punishment measures will slow down the speed of the public choosing the strategy of not wearing masks. The speed of the public evolving to the stable strategy under the dominance of super-expected benefits is faster than that under the dominance of expected benefits.Practical implicationsThe study considers the impact of stochastic factors on public prevention and control strategies and provides decision-making support and theoretical guidance for the scientific prevention of the normalized public.Originality/valueTo the best of the authors’ knowledge, no research has considered the impact of different stochastic interference intensities on public prevention and control strategies. Therefore, this paper can be seen as a valuable resource in this field.