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Traditional grey models are integer order whitening differential models; these models are relatively effective for the prediction of regular raw data, but the prediction error of irregular series or shock series is large, and the prediction effect is not ideal.

The new model realizes the dynamic expansion and optimization of the grey Bernoulli model. Meanwhile, it also enhances the variability and self-adaptability of the model structure. And nonlinear parameters are computed by the particle swarm optimization (PSO) algorithm.

Establishing a prediction model based on the raw data from the last six years, it is verified that the prediction performance of the new model is far superior to other mainstream grey prediction models, especially for irregular sequences and oscillating sequences. Ultimately, forecasting models are constructed to calculate various energy consumption aspects in Chongqing. The findings of this study offer a valuable reference for the government in shaping energy consumption policies and optimizing the energy structure.

It is imperative to recognize its inherent limitations. Firstly, the fractional differential order of the model is restricted to 0 < a < 2, encompassing only a three-parameter model. Future investigations could delve into the development of a multi-parameter model applicable when a = 2. Secondly, this paper exclusively focuses on the model itself, neglecting the consideration of raw data preprocessing, such as smoothing operators, buffer operators and background values. Incorporating these factors could significantly enhance the model’s effectiveness, particularly in the context of medium-term or long-term predictions.

This contribution plays a constructive role in expanding the model repertoire of the grey prediction model. The utilization of the developed model for predicting total energy consumption, coal consumption, natural gas consumption, oil consumption and other energy sources from 2021 to 2022 validates the efficacy and feasibility of the innovative model.

These findings, in turn, provide valuable guidance and decision-making support for both the Chinese Government and the Chongqing Government in optimizing energy structure and formulating effective energy policies.

This research holds significant importance in enriching the theoretical framework of the grey prediction model.

The highlights of the paper are as follows:

1. A novel grey Bernoulli prediction model is proposed to improve the model’s structure.

2. Fractional derivative, fractional accumulating generation operator and Bernoulli equation are added to the new model.

3. The proposed model can achieve full compatibility with the traditional mainstream grey prediction models.

4. Energy consumption in Chongqing verifies that the performance of the new model is much better than that of the traditional grey models.

5. The research provides a reference basis for the government to formulate energy consumption policies and optimize energy structure.

A novel grey Bernoulli prediction model is proposed to improve the model’s structure.

Fractional derivative, fractional accumulating generation operator and Bernoulli equation are added to the new model.

The proposed model can achieve full compatibility with the traditional mainstream grey prediction models.

Energy consumption in Chongqing verifies that the performance of the new model is much better than that of the traditional grey models.

The research provides a reference basis for the government to formulate energy consumption policies and optimize energy structure.

This paper aims to calculate the mixed‐mode stress intensity factors (SIFs) of a 3D crack meeting the interface in a bimaterial under shear loading by a hypersingular integral equation (HIE) method, And further to assess the accuracy of numerical solutions for the mixed mode SIFs along the crack front.

A 3D crack modeling is reduced to solving a set of HIEs. Based on the analytical solutions of the singular stress field around the crack front, a numerical method for the HIEs is proposed by a finite‐part integral method, where the displacement discontinuities of the crack surface are approximated by the product of basic density functions and polynomials. Using FORTRAN program, numerical solutions of the mixed‐mode SIFs of some examples are presented.

The numerical method is proved to be an effective construction technique. The numerical results show that this numerical technique is successful, and the solution precision is satisfied.

This work takes further steps to improve the fundamental systems of HIE for its application in the fields of arbitrary shape crack problems. Propose several techniques for numerical implementation, which could increase the efficiency and accuracy of computation.

Whenever there is a structure containing the 3D crack, the analysis method described in this paper can be utilized to find the critical configurations under which the structure may be most vulnerable. In such cases, the strength predictions would be safer if the crack could be taken into account.

This paper is the first to apply HIE method to analyzing the mixed‐mode crack meeting the interface in 3D dissimilar materials. Numerical solutions of the mixed‐mode SIFs can give the satisfied solution precision.

The purpose of this paper is to present special nine‐node quadrilateral elements to discretize the un‐cracked boundary and the inclined surface crack in a transversely isotropic cuboid under a uniform vertical traction along its top and bottom surfaces by a three‐dimensional (3D) boundary element method (BEM) formulation. The mixed‐mode stress intensity factors (SIFs), K_I, K_II and K_III, are calculated.

A 3D dual‐BEM or single‐domain BEM is employed to solve the fracture problems in a linear anisotropic elastic cuboid. The transversely isotropic plane has an arbitrary orientation, and the crack surface is along an inclined plane. The mixed 3D SIFs are evaluated by using the asymptotical relation between the SIFs and the relative crack opening displacements.

Numerical results show clearly the influence of the material and crack orientations on the mixed‐mode SIFs. For comparison, the mode‐I SIF when a horizontal rectangular crack is embedded entirely within the cuboid is calculated also. It is observed that the SIF values along the crack front are larger when the crack is closer to the surface of the cuboid than those when the crack is far away from the surface.

The FORTRAN program developed is limited to regular surface cracks which can be discretized by the quadrilateral shape function; it is not very efficient and suitable for irregular crack shapes.

The evaluation of the 3D mixed‐mode SIFs in the transversely isotropic material may have direct practical applications. The SIFs have been used in engineering design to obtain the safety factor of the elastic structures.

This is the first time that the special nine‐node quadrilateral shape function has been applied to the boundary containing the crack mouth. The numerical method developed can be applied to the SIF calculation in a finite transversely isotropic cuboid within an inclined surface crack. The computational approach and the results of SIFs are of great value for the modeling and design of anisotropic elastic structures.

The paper aims to propose a new mathematical model for allocation and scheduling of vessels at multiple marine container terminals of the same port, considering the access channel depth variations by time of day.

This paper proposes a new mathematical model for allocation and scheduling of vessels at multiple marine container terminals of the same port, considering the access channel depth variations by time of day. The access channel serves as a gate for vessels entering or leaving the port. During low-depth tidal periods the vessels with deep drafts have to wait until the depth of the access channel reaches the required depth.

A number of numerical experiments are performed using the operational data collected from Port of Bandar Abbas (Iran). Results demonstrate that the suggested methodology is able to improve the existing port operations and significantly decrease delayed vessel departures.

The contribution of this study to the state of the art is a novel mathematical model for allocation and scheduling of vessels at multiple terminals of the same port, taking into consideration channel depth variations by time of day. To the best of the authors’ knowledge, this is the first continuous berth scheduling linear model that addresses the tidal effects on berth scheduling (both in terms of vessel arrival and departure at/from the berth) at multiple marine container terminals.

The ecological environment of the Loess Plateau, China, is extremely fragile under the context of global warming. Over the past two decades, the vegetation of the Loess Plateau has undergone great changes. This paper aims to clarify the response mechanisms of vegetation to climate change, to provide support for the restoration and environmental treatment of vegetation on the Loess Plateau.

The Savitsky–Golay (S-G) filtering algorithm was used to reconstruct time series of moderate resolution imaging spectroradiometer (MODIS) 13A2 data. Combined with trend analysis and partial correlation analysis, the influence of climate change on the phenology and enhanced vegetation index (EVI) during the growing season was described.

The S-G filtering algorithm is suitable for EVI reconstruction of the Loess Plateau. The date of start of growing season was found to gradually later along the Southeast–Northwest direction, whereas the date of the end of the growing season showed the opposite pattern and the length of the growing season gradually shortened. Vegetation EVI values decreased gradually from Southeast to Northwest. Vegetation changed significantly and showed clear differentiation according to different topographic factors. Vegetation correlated positively with precipitation from April to July and with temperature from August to November.

This study provides technical support for ecological environmental assessment, restoration of regional vegetation coverage and environmental governance of the Loess Plateau over the past two decades. It also provides theoretical support for the prediction model of vegetation phenology changes based on remote sensing data.

Market integration in China is still progressing, while the border effects of trade among regions still exist. The question of whether eliminating or weakening regional bias can promote of China's agricultural trade still remains an important issue. This paper analyzes the impact of regional bias on China's agricultural trade.

This paper constructs a pure exchange computable general equilibrium model of nine regions and three sectors, and analyzes the impact of regional bias on China's regional agricultural trade; Comparing the differences of regional bias on China's inter-regional and external agricultural trade, the paper especially analyzes the impact of the agricultural imports and exports in eight regions of China.

The results show that regional bias has had substantial impacts on China's agricultural trade. Elimination of regional bias would therefore increase China's agricultural exports and imports by factors of 1.32 and 1.63, respectively while its agricultural trade deficit would increase by 84%. Inter-regional agricultural trade in China would increase by 3.53 times. With the elimination of regional bias, the Northern coastal, Central and Northwestern regions would have the largest increase in inter-regional agricultural trade. Unlike the Northern coastal region, inter-regional agricultural import in the Central and Northwestern regions tends to be greater than inter-regional agricultural exports.

This paper thus aims to fill existing gap in investigating the impacts of regional bias on China's agricultural trade. Firstly, the model proposed in this paper does not only consider the linkage between the agricultural and non-agricultural sectors, but also the inter-regional agricultural trade linkages of the different regions in China. Secondly, the authors decompose home bias into national and regional biases and assess how regional bias affects agricultural trade of the various regions of China.

This study aims to evaluate a new fusion technique of visual and textual clusters of objects from a real multimedia data-driven collection to improve the performance of multimedia applications.

The authors focused on using multi-criteria for clustering texts and images. The algorithm consists of these steps: first is text representation using the statistical method of weighting, second is image representation using a bag of words feature descriptors methods and finally application of multi-criteria clustering.

As an application for event detection based on social multimedia data, in particular, Flickr platform. Several experiments were conducted to choose the appropriate parameters for a better scheme of clustering. The new approach achieves better performance when aggregate text clustering is done with image clustering for event detection.

Further researches would be investigated on other social media platforms such as Facebook and Twitter for a generalization of the technique.

This study contributes to multimedia data mining through the new fusion technique of clustering. The technique has its root in such strong field as the field of multi-criteria clustering and decision-making support.

For underwater hydraulic machinery, the unique structure significantly enhances the three-dimensional non-uniformity of turbulence within the flow domain and high Reynolds number turbulence introduces complex effects on the machinery. Therefore, studying the turbulent flow characteristics in underwater hydraulic machinery is crucial for system stability.

This paper conducts a numerical analysis on a specific type of underwater hydraulic machinery. A numerical calculation model is established under stable inflow conditions to analyze the flow trends and pressure changes at different flow speeds. Subsequently, structural modifications are made to the underwater hydraulic machinery, and the characteristics of the velocity field, pressure field and vorticity distribution under different model parameters are analyzed.

The results indicate that changes in internal structure have a certain impact on flow characteristics. When the structural changes are significant, the fluid flow becomes more complex and pressure fluctuations become more intense. The research findings provide a scientific basis and theoretical guidance for the structural design of underwater hydraulic machinery and have significant research implications for controlling fluid-induced noise.

Affected by the inherent structural characteristics of the flow channel structure, the flow direction of the high-speed water flow changes drastically in the flow channel, so it is of great significance to study its flow characteristics for the stability of the system.

The purpose of this paper is to provide an improved Mie-Grüneisen mixture model to simulate underwater explosion (UNDEX).

By using Mie-Grüneisen equations of state (EOS) to model explosive charge, liquid water and solid structure, the whole fluid field is considered as a multi-phases mixture under Mie-Grüneisen EOS. Then by introducing auxiliary variables in Eulerian model and using mass fraction to establish a diffusion balance, a new improved Mie-Grüneisen mixture model is presented here. For the new reconstructed mixture model, a second order MUSCL scheme with TVD limiter is employed to solve the multi-phase Riemann problem.

Numerical examples show that the results obtained by Mie-Grüneisen mixture model are quite closed to theoretical and empirical data. The model can be also used in 2-D fluid-structure problem of UNDEX effectively and it is proved that the deformation of structure can be clearly described by mass fraction.

The FVM model based on mass fraction can only describe the motion of compressible material under impact. Material failure or large deformation needs a modification about the EOS or implementations of other models (i.e. FEM model).

An improved non-oscillation Mie-Grüneisen mixture model, which based on mass fraction, is given in the present paper. The present Mie-Grüneisen mixture model provides a simplified and efficient way to simulate UNDEX. The feasibility of this model to simulate the detonation impacts on different mediums, including water and other metal mediums, is tested and verified here. Then the model is applied to the simulation of underwater contact explosion problem. In the simulation, deformation of structure under explosion loads, as well as second shock wave, are studied here.

Existing studies suggested that there is a nonlinear relationship between lean production adoption and organizational performance. Lean production adoption is a gradual process, and the application status of lean tools will affect enterprise performance. The existing literature has insufficiently explored the nonlinear relationship of the lean tools application status on operational performance and environmental performance using the same theoretical framework. A combination approach of interpretative structural modeling (ISM) and Bayesian networks was proposed in this paper, which was used to analyze the complex relationship between lean tools application status with operational and environmental performance.

ISM was used to analyze the inter-relationship of 17 lean tools identified from the lean literature and construct the lean tools structure model providing reference for building Bayesian network. By calculating the prior and conditional probabilities within the lean tools and between the lean tools with the operational and environmental performance, a Bayesian simulation model was constructed and used to analyze the performance outcomes under different lean tools application status.

The performance simulation result – representing by the probability of three performance levels as good, average and poor – shows inconsistent changes with the changing of lean tools application status. By comparing the changes of operational performance and environmental performance, it can be found that environmental performance is less sensitive to the change of lean tools application status than operational performance.

Using the integrated ISM–Bayesian network approach, the results indicated a nonlinear relationship between lean tools with operational and environmental performance and provided a reference for the exploration of the nonlinear relationship between lean tools and performance. This research further calls for exploring the S-curve relationship between lean tools and environmental performance.