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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 paper aims to elucidate the pivotal role of Digital Twin (DT) technology in addressing the adverse impacts of Urban Heat Island (UHI) and consolidate the fragmented knowledge of DT technology in urban environments by identifying applied actions, proposing an approach and revealing challenges for tackling UHI effects.

Using a systematic literature review, 24 materials were retrieved from scholarly databases to provide a comprehensive understanding of DT technology and propose a conceptual framework for mitigating UHI effects.

The results revealed three major study categories within the DT and UHI domains: (1) DT-enabled actions for urban greenery optimisation, (2) DT implementation for enhancing resilience in urban planning and (3) increasing the fidelity level of DT for addressing UHI effects. Additionally, this paper introduces REFLECT, a conceptual DT-enabled framework consisting of seven layers: Retrieve, Establish, Facilitate, Lump, Examine, Cognition and Take. The framework proposes developing a systems-based model with identifiable scopes, strategies and factors through a multilayered platform, specifying model input, process and output towards mitigating UHI effects.

This paper contributes to the discourse on sustainable urban development by highlighting the challenges associated with DT technology in mitigating UHI. It introduces a conceptual framework to demonstrate applications and directions for developing innovative solutions to unlock the full potential of DT technology in mitigating UHI effects.

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.

The theme park industry has attracted wide attention and visitors’ perceptions are key to improving theme park management. Applying the cognitive-affective theory, this study aims to explore various cognitive attributes and affective attitudes and how they affect the overall theme park image.

A mixed research method was used to analyze tourists’ cognitive, affective and overall evaluations of theme parks through text mining and logistic regression and to verify their internal relationships.

Study 1 confirms the impact of six features of theme parks, including food and beverage consumption, merchandising, spatiality, immersive technologies, interactive performances and thematization. Study 2 reveals that finer-grained emotions such as goodness, sadness, disgust, surprise, fear, joy and anger are present in visitor reviews. Study 3 confirms the significant influence of cognitive characteristics and emotions related to theme parks on the overall image through regression analysis. The findings carry meaningful implications for theme park managers, offering guidance on customer needs, perceived negative attributes and how to improve visitor experiences.

This study explores the attribute characteristics of cognitive and affective images of theme parks and their influence on the overall image, thereby enriching the research on the connotations of cognitive-affective theory. In particular, this study introduces and quantitatively analyses the concept of theme parks for the first time through a large-scale data analysis, which empirically reconciles the contradictions of previous reviews of different definitions of theme parks.

主题公园评论：文本挖掘的认知特征和情感如何决定主题公园形象

摘要

主题公园行业备受关注, 而游客的看法是改进主题公园管理的关键所在。本研究运用认知-情感理论, 旨在探索游客评论的认知属性与情感态度, 以及它们如何影响主题公园的整体形象。

采用混合研究方法, 通过文本挖掘和逻辑回归分析游客对主题公园的认知、情感及总体评价, 并验证它们之间的内在关系。

研究1证实了主题公园的六个特征所产生的影响, 包括餐饮消费、商品销售、空间性、沉浸式技术、互动表演和主题化。研究2表明, 游客评价中存在更细化的情感, 如好感、悲伤、厌恶、惊讶、恐惧、喜悦和愤怒。研究3通过回归分析证实了与主题公园相关的认知和情感特征对整体形象具有显著影响。这些研究结果对主题公园管理者具有重要意义, 为了解客户需求、识别负面属性以及如何改善游客体验提供了指导。

本研究对主题公园认知和情感形象的属性特征及其对整体形象的影响进行了探索, 从而丰富了认知-情感理论内涵。特别是本研究首次通过引入大规模数据并量化分析了主题公园的概念, 从实证角度调和了以往针对主题公园不同定义的相关评论中存在的矛盾。

Reseñas de parques temáticos: cómo la minería de textos de las características cognitivas y las emociones pueden determinar la imagen del parque temático

Resumen

El sector de los parques temáticos ha atraído una gran atención y las percepciones de los visitantes son clave para mejorar su gestión. Aplicando la teoría cognitivo-afectiva, este estudio pretende explorar diversos atributos cognitivos y actitudes afectivas, y cómo afectan a la imagen global del parque temático.

Se adoptó un enfoque de investigación de métodos mixtos para analizar las evaluaciones cognitivas, afectivas y globales de los turistas sobre los parques temáticos mediante minería de textos y regresión logística, y para validar la relación intrínseca entre ellas.

El estudio 1 confirmó el impacto de seis características de los parques temáticos, como el consumo de alimentos y bebidas, el merchandising, la espacialidad, las tecnologías inmersivas, los espectáculos interactivos y la tematización. El estudio 2 reveló la presencia de emociones más sutiles en las evaluaciones de los visitantes, como la bondad, la tristeza, el asco, la sorpresa, el miedo, la alegría y la ira. El estudio 3 confirmó, mediante un análisis de regresión, que las características cognitivas y las emociones asociadas a los parques temáticos tienen un efecto significativo en la imagen global. Estas conclusiones tienen importantes implicaciones para los gestores de los parques temáticos, ya que proporcionan orientación para comprender las necesidades de los clientes, identificar los atributos negativos percibidos y saber cómo mejorar las experiencias de los visitantes.

Este estudio explora las características de los atributos de las imágenes cognitivas y afectivas de los parques temáticos y su impacto en la imagen global, enriqueciendo así la investigación sobre las connotaciones de la teoría cognitivo-afectiva. En particular, este estudio introduce y analiza cuantitativamente por primera vez el concepto de parque temático mediante un análisis de datos a gran escala, que concilia empíricamente las contradicciones que existían en revisiones anteriores de las distintas definiciones de parque temático.

After the standstill generated by the COVID-19 outbreak, airlines were forced to adapt their operations and strategies to the new market requirements and constraints both in terms of supply and demand. The initial recovery included many short-term decisions for survival. Yet, as the market recovered, sometimes in new forms, airlines rebuilt their networks for a new long-term future. In this chapter, we compare the pre- and postpandemic network configurations of a selection of European airlines using a combination of network structure, topology, and connectivity indicators, which help understand airlines' network economics. As a general trend, low-cost carriers recovered faster than full-service ones, in many cases already exceeding prepandemic supply volumes. However, our study shows the high heterogeneity of responses and postpandemic network structures across business models. While some airlines kept very similar structures, adapting to the demand change, some opted for a bolder strategy, growing their networks compared to prepandemic levels. Also, in some cases, new regulations or other external events forced the changes in networks. Finally, although in 2022 data still showed long-haul markets a little behind compared to prepandemic figures, signs such as the continued passenger increase and the ramp up of aircraft orders by airlines point toward a full recovery leading back to a sector based on continued traffic growth.