Balance Method Research Articles

Balancing versus modelling in weighted analysis of non-randomised studies with survival outcomes: A simulation study.

Weighting methods are widely used for causal effect estimation in non-randomised studies. In general, these methods use the propensity score (PS), the probability of receiving the treatment given the covariates, to arrive at the respective weights. All of these "modelling" methods actually optimize prediction of the respective outcome, which is, in the PS model, treatment assignment. However, this does not match with the actual aim of weighting, which is eliminating the association between covariates and treatment assignment. In the "balancing" approach, covariates are thus balanced directly by solving systems of numerical equations, explicitly without fitting a PS model. To compare modelling, balancing and hybrid approaches to weighting we performed a large simulation study for a binary treatment and a survival outcome. For maximal practical relevance all simulation parameters were selected after a systematic review of medical studies that used PS methods for analysis. We also introduce a new hybrid method that uses the idea of the covariate balancing propensity score and matching weights, thus avoiding extreme weights. In addition, we present a corrected robust variance estimator for some of the methods. Overall, our simulations results indicate that balancing approach methods work worse than expected. However, among the considered balancing methods, entropy balancing consistently outperforms the variance balancing approach. All methods estimating the average treatment effect in the overlap population perform well with very little bias and small standard errors even in settings with misspecified propensity score models. Finally, the coverage using the standard robust variance estimator was too high for all methods, with the proposed corrected robust variance estimator improving coverage in a variety of settings.

A simple matrix method for the force balancing of planar multi-degree-of-freedom linkages

The shaking or fluctuating reaction forces produced by the moving links of a mechanism negatively impact its adequate performance due to the inherent generation of base vibrations, fatigue stresses, accuracy loss of the end-effector or moving platform, and so on. To increase the functionality and durability of the mechanism is therefore strongly advised to eliminate these parasitic forces. This article provides the balancing conditions for planar multi-degree-of-freedom linkages by canceling the total shaking force generated by the moving links of the mechanism. The method avoids the classical computation of the total linear momentum employed in existing methods. The balancing of three representative linkages proves the reliability of the proposed method.

#596 The Borg Scale—efficient and safe for exercise prescription in self-administered balance and strength exercise in patients with CKD

Abstract Background and Aims With the continued rise in chronic kidney disease (CKD), there is a critical need for sustainable, home-based exercise interventions. While supervised, centre-based exercise improves physical performance in CKD patients, unsupervised, self-administered exercise poses challenges in ensuring adherence, safety, and efficacy. This study investigates the Borg Rating of Perceived Exertion (RPE) scale, a subjective measure of exertion, as a method for prescribing and monitoring the intensity of balance and strength exercise in non-dialysis dependent CKD patients. The aims of this study were: Method This sub study of the RENEXC-trial included 148 patients with CKD stages 3-5, with a mean age of 66 ± 14 years and mean measured GFR of 22 ± 8 ml/min/1.73 m2. Patients were prescribed 90 minutes/week of balance or strength exercise at a Borg RPE of 13-17 (corresponding to an exercise intensity of somewhat hard to very hard), along with 60 minutes/week of endurance exercise. Exercise programs were individually prescribed by a physiotherapist according to randomization and each patient's baseline performance and were performed at home or in a gym according to the patient's preference. Duration and RPE of the performed exercise were reported in an exercise diary. Progress was monitored by the physiotherapist through phone contact, every week for the first three months of the study and every other week for the rest of the study year. The continuous follow up provided motivation and enabled adjustments of the exercise program to maintain the goal RPE, adapt intensity and the weekly duration of exercise. Outcome measures included the Berg Balance Scale (BBS) and Functional Reach Test (FRT), the 30-second sit-to-stand test (30STS) and isometric quadriceps strength (IQS). Balance and strength measures were evaluated at baseline and after 12 months of exercise. Previous publications of the RENEXC-trial showed no difference between patients who performed balance exercise and patients who performed strength exercise; therefore, this sub-study analysed all included patients as one group. Results Of 148 participants, 112 completed the study. At 12 months, 79% reported performed exercise, with 86% of these patients adhering to the prescribed intensity. The median (25th-75th percentile) exercise intensity was a RPE of 14 (13-15) on the Borg scale, and the median (min-max) exercise duration was 48 (0-241) minutes/week. Only 18% of the patients reached the 90-minute/week target. No exercise-related incidents were reported. Significant improvements were noted in BBS (p = 0.0464), FRT (p = 0.009), 30STS (p = 0.047), and IQS (right/left p = 0.022 / p = 0.049). Conclusion The Borg RPE scale is an effective and safe method for prescribing and monitoring self-administered balance and strength exercise in patients with CKD. Using the Borg scale for prescribing and monitoring exercise intensity during balance and strength exercise resulted in a good level of adherence to the 12-months exercise program and the prescribed exercise intensity. As no exercise related incidents were reported, we conclude that the self-administered exercise was safe to perform. Significant improvements in balance and strength were observed with a moderate to high exercise intensity prescription within a wide range of performed weekly duration of exercise, suggesting the Borg scale's value in exercise prescription in both well- and deconditioned patients with CKD. These findings show that the integration of the Borg scale into routine exercise prescription in people with CKD can promote patient autonomy and efficient resource utilization in healthcare.

Design and Analysis of Low-Gravity Simulation Scheme for Mars Ascent Vehicle

The sample carried back by the Mars Ascent Vehicle (MAV) is a potential flagship mission of deep space exploration in recent years. A low-gravity simulation experiment is an effective method and a necessary stage for verifying the performance of the MAV launch dynamic in Earth’s gravity. In this paper, the uniqueness of low-gravity simulation is illustrated by the classical pulley balance method for the high dynamic process of a test model of the MAV. Its movement direction is the same as the compensation force, which leads to the relaxation of the sling and the failure of the compensation force in traditional cable suspension. Here, three cable suspension schemes including an improved pulley balancing scheme based on a coordinate transformation scheme and based on a dynamic pulley group scheme are proposed. For the actual launch condition of the MAV, the motion state of the ascent under the schemes and the real Mars launch are compared, which proves the feasibility of the schemes. Among them, the improved pulley balancing scheme has the best gravity compensation effect, and the error between the average value and the required value is the smallest, only 1%.

Improved pediatric ICU mortality prediction for respiratory diseases: machine learning and data subdivision insights

The growing concern of pediatric mortality demands heightened preparedness in clinical settings, especially within intensive care units (ICUs). As respiratory-related admissions account for a substantial portion of pediatric illnesses, there is a pressing need to predict ICU mortality in these cases. This study based on data from 1188 patients, addresses this imperative using machine learning techniques and investigating different class balancing methods for pediatric ICU mortality prediction. This study employs the publicly accessible “Paediatric Intensive Care database” to train, validate, and test a machine learning model for predicting pediatric patient mortality. Features were ranked using three machine learning feature selection techniques, namely Random Forest, Extra Trees, and XGBoost, resulting in the selection of 16 critical features from a total of 105 features. Ten machine learning models and ensemble techniques are used to make accurate mortality predictions. To tackle the inherent class imbalance in the dataset, we applied a unique data partitioning technique to enhance the model's alignment with the data distribution. The CatBoost machine learning model achieved an area under the curve (AUC) of 72.22%, while the stacking ensemble model yielded an AUC of 60.59% for mortality prediction. The proposed subdivision technique, on the other hand, provides a significant improvement in performance metrics, with an AUC of 85.2% and an accuracy of 89.32%. These findings emphasize the potential of machine learning in enhancing pediatric mortality prediction and inform strategies for improved ICU readiness.

On the displacement control performance of base-isolated structures incorporating nonlinear negative stiffness device

Low-frequency dominant far-field harmonic-like long period ground motions (FGMs) excitations have the potential to amplify the seismic response of base-isolated structures (BIS) and may result in isolator displacements exceeding their maximum limits. The application of negative stiffness devices (NSD) in isolated structures primarily focuses on SDOF systems, which fails to capture the displacement response of the superstructure on the isolation story. To address this issue, this study proposes the application of NSD to a 2DOF system in a BIS, with root mean square value as the metric for displacement transmissibility. Firstly, the displacement transmissibility of base-isolated structures with negative stiffness devices (BIS-NSD) and BIS is derived using the triple-harmonic balance (T-HB) method and the single-harmonic balance (S-HB) method, respectively. Subsequently, the applicability of the T-HB method and the S-HB method in obtaining analytical solution for the displacement transmissibility of BIS-NSD and BIS is revealed and validated through numerical solution. Parameters are selected based on fixed-point theorem for comparative analysis of the displacement and acceleration transmissibility between BIS-NSD and BIS. Finally, a comparative analysis between BIS-NSD and BIS under FGMs confirms the application advantages of NSD. The results indicate that compared to BIS, BIS-NSD significantly reduces the displacement transmissibility of the superstructure and the isolation story in the low-frequency range. As the primary resonance frequency decreases, NSD widens the vibration bandwidth of BIS. BIS-NSD effectively mitigates the increase in displacement caused by low-frequency ground motions. The acceleration transmissibility demonstrates that, without sacrificing the acceleration of the superstructure, it effectively controls the displacement of the isolation story.

Application of Numerical Bifurcation Tracking Strategy to Blade-Tip/Casing Interactions in Aircraft Engines

Abstract Building on the regularized-Lanczos harmonic balance method (RL-HBM), a previously developed frequency method, this paper presents a numerical bifurcation tracking strategy dedicated to high-dimensional nonlinear mechanical systems. In order to demonstrate its applicability to industrial applications, it is here used to obtain original results in the context of blade-tip/casing interactions in aircraft engines. The emphasis is put specifically on the tracking of predicted limit point (LP) bifurcations as key parameters—such as the amplitude of the aerodynamic forcing applied on the blade, the friction coefficient or the operating clearances—vary. Overall, presented results underline that the employed frequency method is well-suited to tackle the numerical challenges inherent to such computations on high-dimensional systems. For the mechanical system of interest, the industrial fan blade National Aeronautics and Space Administration (NASA) rotor 67, it is shown that the application of the presented strategy yields an efficient way to identify isolated branches of solutions, which may be of critical importance from a design standpoint.

Ultra-low frequency vibration energy harvesting of piezoelectric vibration systems with an adjustable device

Energy harvesting from external Ultra-low frequency vibrations is currently attracting a lot of attention. However, for the same system, it is difficult to satisfy the need for more efficient energy harvesting in a variety of external environments. Accordingly, an adjustable gearing device connected to the energy harvesting system is used herein for adapting energy harvesting to a wide range of external environments. The device uses four symmetrical inclined springs. One end of the springs is connected to a gear and the other end to a mass element. The geometrical parameters of the system can be varied by rotating the gears, thus varying the dynamic stiffness of the system. The kinetic equations of the system are derived and their nonlinear terms are Taylor-expanded. The amplitude-frequency response curve of the system is obtained by solving using the harmonic balance method. Multi-color plots of RMS values of induced voltage and electric power are obtained using the fourth-order Runge-Kutta method. The results show that the device has excellent adjustable performance. Adjusting the rotation angle of the gears can change the soft and hard characteristics of the system's dynamic stiffness and the intrinsic frequency, thus improving the system's energy harvesting performance in different environments.

A Simple Method for Estimating Stomatal Aperture from Temperature Measurements on Intact Leaves and Wet and Dry Artificial Reference Leaves

Environmental control in greenhouse horticulture is essential for providing optimal conditions for plant growth and achieving greater productivity and quality. To develop appropriate environmental management practices for greenhouse horticulture through sensing technologies for monitoring the environmental stress responses of plants in real time, we evaluated the relative value of the stomatal opening to develop a technology that continuously monitors stomatal aperture to determine the moisture status of plants. When plants suffer from water stress, the stomatal conductance of leaves decreases, and transpiration and photosynthesis are suppressed. Therefore, monitoring stomatal behavior is important for controlling plant growth. In this study, a method for simply monitoring stomatal conductance was developed based on the heat balance method. The stomatal opening index (SOI) was derived from heat balance equations on intact tomato leaves, wet reference leaves, and dry reference leaves by measuring their temperatures in a growth chamber and a greenhouse. The SOI can be approximated as the ratio of the conductance of the intact leaf to the conductance of the wet reference leaf, which varies from 0 to 1. Leaf temperatures were measured with infrared thermometry. The theoretically and experimentally established SOI was verified with tomato plants grown hydroponically in a greenhouse. The SOI derived by this method was consistent with the leaf conductance measured via the porometer method, which is a standard method for evaluating actual leaf conductance that mainly consists of stomatal conductance. In conclusion, the SOI for the continuous monitoring of stomatal behavior will be useful not only for studies on interactions between plants and the environment but also for environmental management, such as watering at plant production sites.

Introduction of Local Resonators to a Nonlinear Metamaterial With Topological Features

Abstract Recent work in nonlinear topological metamaterials has revealed many useful properties such as amplitude dependent localized vibration modes and nonreciprocal wave propagation. However, thus far, there have not been any studies to include the use of local resonators in these systems. This work seeks to fill that gap through investigating a nonlinear quasi-periodic metamaterial with periodic local resonator attachments. We model a one-dimensional metamaterial lattice as a spring-mass chain with coupled local resonators. Quasi-periodic modulation in the nonlinear connecting springs is utilized to achieve topological features. For comparison, a similar system without local resonators is also modeled. Both analytical and numerical methods are used to study this system. The dispersion relation of the infinite chain of the proposed system is determined analytically through the perturbation method of multiple scales. This analytical solution is compared to the finite chain response, estimated using the method of harmonic balance and solved numerically. The resulting band structures and mode shapes are used to study the effects of quasi-periodic parameters and excitation amplitude on the system behavior both with and without the presence of local resonators. Specifically, the impact of local resonators on topological features such as edge modes is established, demonstrating the appearance of a trivial bandgap and multiple localized edge states for both main cells and local resonators. These results highlight the interplay between local resonance and nonlinearity in a topological metamaterial demonstrating for the first time the presence of an amplitude invariant bandgap alongside amplitude dependent topological bandgaps.

Fish oil replacement with different vegetable oils in Onychostoma macrolepis: Effects on fatty acid metabolism based on whole-body fatty acid balance method and genes expression.

To evaluate the fatty acid (FA) metabolism status and possibility as a DHA source of farmed Onychostoma macrolepis, a total of 168 fish (2.03 ± 0.23 g) were fed four diets supplemented with fish oil (FO), linseed oil (LO), soybean oil (SO), and a mixture of LO and SO oil (MO), respectively, for 70 days. Body FA compositions were modified reflecting dietary FAs. Comparing liver and intestine fatty acids with fish fed four diets, the content of ARA in fish fed SO was significantly higher than others (P < 0.05), but showed no difference in muscle. The tissue FA profile showed that the FO-fed group successfully deposited DHA, while the LO-fed group converted ALA to DHA effectively, as well as the liver and intestine EPA was notably highest in the FO group, whereas no difference between the FO and LO group in the muscle. The FA results showed that the DHA contents in the muscle of Onychostoma macrolepis are at a medium-high level compared with several other fish species with the highest aquaculture yield. Correspondingly, in the fish fed diet with LO, SO, and MO, the genes of most FA biosynthesis, transportation, and transcriptional regulation factors were increased in the liver and muscle, but no significant difference was observed in the gene expression of Elovl4b, FATP1, and FABP10 in the muscle. In addition, the enzyme activity involved in PUFA metabolism was higher in fish fed vegetable oil-based diets, corroborating the results of the gene expression. Increased in vivo elongase and desaturase (Δ5, Δ6, and Δ9) activities were recorded in fish fed fish oil-devoid diets, which resulted in the appearance of products associated with elongase and desaturase activities in fish. Besides, as the specific n-3 PUFA synthesis substrate, the dietary supplementation of ALA not only retains most of the nutrition value but also ensures the muscular texture, such as fiber diameter and density. It is concluded that farmed O. macrolepis owns strong n-3 LC-PUFA biosynthetic capacity and high DHA contents so it can be a good DHA source for the population.

A distributed load balancing method for IoT/Fog/Cloud environments with volatile resource support

A distributed load balancing method for IoT/Fog/Cloud environments with volatile resource support

Multi-Passage harmonic balance method for flutter prediction in multi-row configurations

A multi-passage harmonic balance method is presented for flutter prediction in multi-row configurations, and particular focus is on simulation of more than two blade rows. The unsteady flows in such configurations contain two kinds of multiple perturbations: one refers to those who have different frequencies and the other one refers to those who have the same frequency but different inter-blade phase angles (IBPAs). Most of current harmonic balance methods only consider the former one and the applications have been restricted to two-blade-row configurations. In the few studies that consider more rows, a one-to-one correspondence assumption between frequency and IBPA is usually made putting extra limitation on the used modes. This motivates our work, and a simple but effective idea is proposed by adding passages adopted per row. The theoretical basis of this work is provided by the spinning mode analysis. The present method is developed based on the time-spectral and multi-frequential form of harmonic balance. The treatment of pitchwise and inter-row boundary conditions in the case of multi passages are particularly addressed. A recently-developed Jacobian-free Newton-Krylov method with a simplified LU-SGS preconditioner is employed to solve the resultant harmonic balance equations. For validation, two typical multi-row flutter cases are investigated. The numerical results show the validity and accuracy of the developed method.

An intelligent assessment method of criminal psychological attribution based on unbalance data

Criminal cases often exhibit imbalance and cannot be extended by data augmentation when classified into attribution types. To solve the problem of unbalance data in offenders’ attribution classification, this paper proposes a criminal psychological attribution assessment model by an improved Balanced TF-Distinguishing IDF method (B-TF-dIDF) and constructed a hybrid network with attention method to fuse numerical and text features for improving the accuracy. First, as a statistical method, B-TF-dIDF is presented to reduce the impact of class-imbalance for extraction of numerical features, in which a balanced element is added to reduce the effects of incorrect type keywords on classification, and a distinguishing element is added to discriminate the types of keywords. Then, an improved hybrid network model composed of Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) is constructed to balance the influence of different lengths of text samples for extracting the semantic features of criminal texts. For evaluating different feature weights by their importance, Spatial Attention is used to improve CNN in the feature maps. Moreover, the self-attention is also performed to re-evaluate the mixed features. Finally, the softmax classifier provides a scientific basis for developing a hierarchical treatment mechanism further. Additionally, we build a criminal data set with labels from real cases for testing. The experiment proved that the proposed model is better than other related methods in various evaluation indicators, including the micro and macro scopes. Moreover, the F1 of minority samples has increased by 6%–8%, indicating that the proposed method can reduce the impact of class-imbalance.

Distributed control of vehicle suspension system based on nonlinear energy sink

Vehicle riding comfort is deteriorated not only by low-order but also by high-order resonance in the suspension system. This paper proposes to arrange the nonlinear energy sink (NES) on the tire to suppress high-order resonance. Two modal resonances can be controlled by a vibration control scheme of the distributed NESs. A dynamic model of a 2-degree-of-freedom quarter-vehicle (2-DOFQV) suspension system integrated with two NESs is established. Then, the model is analyzed approximately analytically by the harmonic balance method (HBM) and verified numerically. Next, the vibration reduction mechanism of the new suspension system is revealed from the perspective of transferred energy. In addition, the vibration reduction effects of the parameters of two NESs are studied. The results of the study show that high-order modal resonance in the suspension system can be effectively controlled by placing an NES of small mass on the tire. Thus, the novelty of this paper is to propose a distributed control strategy for the vehicle suspension system, which can reduce the high-order resonance at the cost of a small mass.

Analysis of the Mathematical Models for Identifying the Thickness of the Fouling Layer in Natural Gas Coolers

This article presents an analysis of three different approaches to the identification of the thickness of the fouling layer inside the pipes of natural gas (NG) coolers. At present, there is no existing simple analytical procedure for the identification of the fouling layer thickness. The authors of this article describe in detail the balance method, which required the use of a large number of physical parameters, changes in their sizes depending on the output temperature of the gas, the temperature of the cooling air, the air quantity, as well as the physical properties of both media. The computational model was robust, and its disadvantage was the iterative computation. The second analysed method was a dimensional analysis. It was applied using the Buckingham’s theorem to express the individual similarity criteria. In this method, 10 simplexes and two complexes were created. The fouling layer thickness, expressed using a derived criterial equation, exhibited real results. The third analysed method was based on analysing selected physical parameters with the use of a multiple regression analysis in MinitabX 18 software. The analysis showed that the fouling layer thickness depended on fewer parameters than the number of parameters assumed in the dimensional analysis or the balance method. The standard deviation that was identified in the multiple linear regression for a double crossflow cooler was 0.0667 and the value of reliability (the coefficient of determination of the multiple linear regression) R2 was 0.9985.

Origami-inspire quasi-zero stiffness structure for flexible low-frequency vibration isolation

As an emerging technology, origami exhibits rich nonlinear static and dynamic properties. However, simulating creases remains a key challenge hindering practice application, especially for volumetric (deformable) origami. Inspired by the bistable behavior and axial-rotational coupling mechanism of triangulated cylindrical origami (TCO), this paper proposes a novel combined truss-spring structure with additional inertial mechanism (TCTS-RIM) for low-frequency vibration isolation. Unlike pure TCO, the TCTS-RIM uses elastic linkages to simulate all creases and modifies crease positions, enhancing physical realization in engineering applications and offering tunable stiffness and inertia on demand. Static analysis shows the modified truss-spring structure in TCTS-RIM has superior quasi-linear negative stiffness compared to pure TCO, which enables a very wide quasi-zero stiffness (QZS) range via linear spring compensation. The wide QZS range for different loads can be realized by setting appropriate structural parameters. From system dynamic equations, nonlinear inertia, nonlinear quadratic force, and nonlinear damping due to RIM are identified and discussed. The Alternating frequency–time harmonic balance method is used to obtain the displacement transmissibility, and its parametric influencing investigations verify that the proposed TCTS-RIM has excellent low-frequency vibration isolation performance and rich tunability. Comparative discussions show the wide QZS range significantly reduces the resonance frequency, broadens the isolation frequency band, and yields superior dynamic performance versus pure TCO isolators. Moreover, equivalent mass, anti-resonance and softening behavior induced by the rotational inertia mechanism further enhance low-frequency vibration isolation performance. An experimental prototype is built, and experimental results validate the correctness of the theoretical analyses. This work presents a simple mechanical implementation of volumetric origami, which may progress the engineering applications of origami and provide a viable approach to low-frequency vibration control.

Static characteristics of a biomimetic robot module driven by water hydraulic artificial muscles resisted with helical spring

Soft modular biomimetic robots, driven by flexible actuators, are extensively used in various fields due to their excellent flexibility, environmental adaptability, and isomorphism. However, existing flexible modules typically possess no more than two degrees of freedom for structural limitations. This paper proposes a biomimetic robot module supported by a spring and actuated by water hydraulic artificial muscles (WHAMs). Combining the mechanical properties of WHAMs and spring, the static model of the soft module was established by force balance method. Moreover, the contraction force coefficient and contraction ratio coefficient of WHAMs were identified through the static characteristics test. The rod length coefficient and stress coefficient of the spring were also identified through the spring bending test. The errors between the experimental results and the model are analyzed and discussed, uncovering the main reasons. The influence of spring pre-compression, spring elasticity coefficient, initial working pressure of WHAM, and the installation distance of WHAM on the motion space of module were analyzed and discussed. This work serves as a guide for the structural design of flexible modules to meet specific requirements and lays the foundation for future research on integrated flexible biomimetic robots driven by WHAMs.

Rational load balancing in collaborated cloud computing environments *

Abstract Optimum efficiency and fault tolerance are the most demanding and challenging issues in the domain of performance and reliability management in cloud computing environments. Optimized resource utilization is a key aspect for yielding efficiency in cloud platforms. Workload balancing through resource sharing is one of the key solutions for attaining performance in cloud environments. In addition, multiple cloud environments join hands to offer performance and fault tolerance through resource sharing. We provide a better and cloud-instances’ priority-based efficient load balancing method for collaborative cloud platforms. The recommended efficient load balancing method shortens the waiting timespan and overcomes the starvation problem of low priority instances in intercloud environments. A functional prototype of the recommended load balancing method was deployed on a physical cloud infrastructure which was setup with the OpenStack cloud software on the Fedora Linux operating system. The pilot project execution findings exhibit a reduction in the timespan borne by instances for executing load balancing. This technique is useful for attaining fault tolerance and efficient resource utilization in intracloud and intercloud environments.

Dynamic balancing method of power distribution and consumption tasks based on state iterative prediction and resource peaking shifting

In the context of the new power system, the widespread access to massive distributed new energy sources has led to the power distribution and consumption tasks characterized by multiple time scales, wide random distribution, and large demand differences, resulting in unpredictable resource peaks in the tasks computing resource demand curve. In view of this situation, a method of forecasting and dynamic balancing of computing resource demand for power distribution and consumption tasks based on state iteration was proposed: firstly, the tasks computing resource demand model was established under the analysis of the attributes and parameter demand of the power distribution and consumption tasks scenario. Secondly, on the basis of the short-term effectiveness prediction of the traditional Markov model, the first-order difference of the state is used for data training to track the state fluctuation, and the historical state and the predicted state are used for state iteration, so as to avoid the convergence of long-term prediction. Finally, a dynamic balancing model is established according to the time-scale characteristics of cyclical and non-cyclical tasks, and the optimal configuration of load imbalance is achieved through the identification and adjustment of historical data and burst data. The simulation results show that the improved Markov model based on first-order difference and state iteration has the short-term accuracy of the traditional model and the long-term traceability of data fluctuations. The dynamic balancing model can combine the characteristics of historical data and burst data to effectively reduce the imbalance of resource demand, and show good ability to cope with resource imbalance deviation.