Planning Period Research Articles

How to ensure an appropriate oral health workforce? Modelling future scenarios for the Netherlands

BackgroundCurrent methods for oral health workforce planning lack responsiveness to dynamic needs, hampering efficiency, equity and sustainability. Effective workforce planning is vital for resilient health care systems and achieving universal health coverage. Given this context, we developed and operationalised a needs-adaptive oral health workforce planning model and explored the potential of various future scenarios.MethodsUsing publicly available data, including the Special Eurobarometer 330 Oral Health Survey, we applied the model in a hypothetical context focusing on the Dutch population’s dental needs from 2022 to 2050. We compared current and future provider supply and requirement and examined, in addition to a base case scenario, several alternative scenarios. These included epidemiological transition scenarios with different oral health morbidity trajectories, skill-mix scenarios with independent oral hygienists conducting check-ups and multiple dental student intake and training duration (5 instead of 6 years) scenarios.ResultsBased on the aforementioned historical data, our model projects that provider requirement will exceed supply for the planning period. If the percentage of people having all natural teeth increases by 10% or 20% in 2032, 34 or 68 additional full-time equivalent (FTE) dentists will be required, respectively, compared to the base case scenario. In the skill-mix scenario, the model indicates that prioritising oral hygienists for check-ups and shifting dentists’ focus to primarily complex care could address population needs more efficiently. Among the student intake and training duration scenarios, increasing intake to 375 and, to a lesser extent, reducing training to 5 years is projected to most effectively close the provider gap.ConclusionsThe study underscores the importance of understanding oral health morbidity trajectories for effective capacity planning. Due to limited dental epidemiological data, projections carry substantial uncertainty. Currently, demand for FTE dentists seems to exceed supply, though this may vary with epidemiological changes. Skill-mix strategies could offer efficiency gains by redistributing tasks, while adjustments in dental intake and training duration could also help address the requirement-supply gap. Resolving dentistry workforce challenges requires a multifaceted approach, including strengthening oral epidemiology projections, addressing the root causes of dental health issues and prioritising harmonious dental public health and general practice prevention measures.

Urban agriculture and urban planning: a case of Bangalore between the 1950s and the 1970s

With urbanisation moving at a faster pace than ever before, discussions on Urban Agriculture (UA) and its role in sustainable development have taken centre stage. The implementation of UA has its challenges, one of them being how urban development frameworks view it. This paper examines the disappearance of a historic UA landscape in Bangalore, India between the 1950s and the 1970s, a period of post-independence urban planning. Using historical records including urban planning documents, government files, and oral histories that I recorded with a traditional community of UA practitioners—the Vahnikula Kshatriya—in Bangalore on their memories of the 1950s–1970s, I argue that colonial frameworks in post-independence urban development plans not only displaced UA but also continues to affect it. This paper highlights the urgent need to change how urban planning in formerly colonised places approaches UA.

Research on the Innovative Path of Brand Development of Graduation Fashion Shows based on the Perspective of New Institutionalism

The 14th Five-Year Plan period is a period for my country to further promote the high-quality and high-efficiency development of "technology, fashion, and green". The training direction of college graduates is constantly changing, and school-enterprise cooperation is constantly subdivided and deepened. As a result, college evaluation is also linked to the employment rate of graduates. It is more required that the graduates trained by the school transform into market-oriented application talents. Therefore, following the three basic principles of highlighting student-centeredness, output orientation, and continuous improvement, introducing the concept of corporate brand show in graduation design to carry out school-enterprise linkage and integrated teaching has become an important task that the fashion design major must face, innovate and explore.

Discussion on the Design Strategy of Shenyang Pocket Park from the Perspective of Child-friendly Health

During the 14th Five-Year Plan period, China proposed to build 100 child-friendly pilot cities. All regions are encouraged to actively carry out the construction of open Spaces such as pocket parks and children, add activity venues suitable for children, and allocate recreational facilities to further promote the construction of urban child-friendly Spaces. Based on this, this paper analyzes the current situation of Shenyang Pocket Park, and puts forward six design improvement strategies from four dimensions of accessibility, safety, interest and comfort, so as to provide new ideas for the construction of child-friendly pocket park.

Spatial-temporal variations and Attribution analysis of SO2 concentration in Beijing-Tianjin-Hebei regions from 2013 to 2022

Based on the monitoring data of air pollutants in Beijing-Tianjin-Hebei regions from 2012 to 2022, the spatial-temporal distribution of SO2 concentration and main influencing factors were analyzed through multi-methods of Daniel trend test, KZ filtering and WRF/CMAQ model simulations. From 2013 to 2022, the annual averaged concentrations of SO2 in Beijing, Tianjin and Hebei regions were all in obvious downward trends, and all passed the Daniel trend test (α=0.01). The annual averaged concentration of SO2 in Beijing, Tianjin and Hebei regions decreased from 26.6~114.3μg·m-3 in 2013 to 3.0~11.0μg·m-3, with the decline rates fluctuating from 2.62~11.81μg/(m3·yr) while the decrease rate of SO2 in Beijing was the lowest. The average annual concentration of SO2 in Tangshan city decreased the most, reaching 92.3% and it changed to be the smallest, about 78.2% in Chengde City. The reduction of coal consumption in the Beijing-Tianjin-Hebei regions significantly reduced atmospheric SO2 emissions and directly reduced the regional average concentration of SO2. Meteorological factors were generally conducive to the diffusion of SO2 concentration during 2013~2022, and the meteorological factors contributed about 0.4~5.5% in 13 cities in Jingjinji area while the contribution of anthropogenic emission reduction was 94.5~99.6%. The inter-annual variation of meteorological factors in summer from 2013 to 2022 was not conducive to the diffusion of SO2 concentration on the whole, and the contribution changed to -52.6 ~ -1.0% in 13 cities. From June to August in summer under the easterly and southerly winds, the SO2 concentration in Beijing was basically twice that of the northerly and westerly winds. The contribution of southwest transport channel to SO2 concentration in Beijing was 33.5%, while it changed to 38.9% in the southeast transport channel. Therefore, strengthening the management and control of air pollutants in surrounding area of Beijing is helpful for Beijing to further reduce the levels of air pollutants and achieve targets of air quality improvement in the 14th Five-Year Plan period.

A multi-objective optimization decision-making methodology for fostering synergies in the water-energy-food nexus

Current decision-making methods within the water-energy-food nexus (WEFN) encounter challenges in practicality, portability, scalability, and accuracy. Optimization methods, integrating site-specific data, offer promise for achieving desired outcomes and enhancing practical decision implementation within WEFN systems. However, these methods still struggle with solving multi-objective and multi-constraint problems, poor performance, and decision-making difficulties. This study developed an optimization method for WEFN systems, which integrates an evolutionary algorithm, swarm intelligence algorithm, multistage evolutionary algorithm, and post-optimization theories to address these issues. Performance results demonstrated that the proposed algorithm outperformed traditional metaheuristic optimization algorithms. Specifically, it excelled in tackling high-dimensional constrained problems, surpassing the classical NSGA series algorithms with a 1.34-fold improvement in the comprehensive performance metric HV. Subsequently, this algorithm combined with knee point post-optimization theory was applied to a typical arid region known for food and energy production. Compared with the business-as-usual scenario, the optimized schemes enhance agricultural benefits, saving 13.3 billion m3 of water over the entire planning period. Meanwhile, sustainable energy implementation would yield potential carbon emission reduction benefits of around 2.8 billion CNY. In summary, the proposed method would successfully provide a paradigm for the synergetic decision-making of WEFN systems.

Resource allocation for Hyphantria cunea invasive management:a novel simulation-based optimization model

In this study, we propose an integrated mixed-integer programming (MIP) model for allocating a limited budget to control a destructive invasive insect endangering the forest vegetation, Hyphantria cunea (H. cunea). Our model seeks to minimize the number of infected and dead trees within a preset planning period, factoring in various infestation scenarios, migration behaviors, resource limitations, intervention timing, and monitoring capabilities. Our modeling framework is novel in the sense that it depicts the transmission process of H. cunea as an infectious compartmental model. Our optimization model is also meaningful because it innovatively bridges the spread dynamics of H. cunea and the optimal resource allocation by using the time-varying number of infected trees that can be accepted in testing and surveillance. Our numerical test data and parameter settings have been collected from large-scale field surveys on H. cunea in Jiangsu Province over the past three years. The scenarios-based method offers significant computational advantages in searching for the best alternatives to real-world size problems in a rational time. Furthermore, our test results specify that the proposed model can not only aid in controlling H. cunea, but also can be adopted as a potential tool for managing other invasive species in the future.

Regional electricity cooperation model for cost-effective electricity management with an emphasis on economic efficiency

Effectively reducing the total electricity cost while ensuring its overall efficiency is vital for the sustainable development of power systems. Herein, we develop a regional cooperation optimization model to enhance the existing power cost model. This is achieved by incorporating power trading scenarios and pollution considerations, leveraging the distinct characteristics of power generation costs from various sources. The developed regional cooperation optimization model simultaneously accounts for production efficiency and overall power costs, ensuring equitable distribution and compensation of benefits among cooperating entities. In addition, the key findings indicate that the interregional cooperation optimization model significantly reduces the total cost of electricity operations in China. Specifically, during the 11th five-year plan period, the total electricity cost in China exhibited a noteworthy decline of USD 50,876 million owing to multi-objective cooperative optimization, constituting 25.99% of the total electricity cost compared with the preoptimization period. This study identifies the eastern and western regions as principal contributors to the cost savings achieved by the interregional cooperative optimization model. Simultaneously, recognizing their significant contributions, it is recommended that the eastern and western regions provide additional cost compensation to other regions to ensure the long-term viability of the cooperative alliance.

The Model of the Armament And Military Equipment Repair System

The purpose of the study, the results of which are presented in the article, is to develop a mathematical model of the process of restoring weapons and military equipment (IWT), taking into account their losses due to combat and operational and technical reasons, as well as the production capabilities of repair and restoration bodies (RVOS) of the first and second levels. For the operational solution of the recovery system planning and managing tasks, it is necessary to have models that allow approximate assessment of the system effectiveness at various levels of management. The hypothesis of the study is to increase the efficiency of restoring weapons and military equipment using the forces and means of military repair bodies, field repair brigades (VRB) in the conditions of the operation, as well as the production capacities of enterprises of the local industrial economic base. As criteria for effectiveness evaluation, the indicators characterizing the combat capabilities of military formations for a certain period of military planning in peacetime and wartime are considered. Research methods are mathematical apparatus of the theory of queuing systems and differential equations of 'dynamics of averages', system analysis, comparative analysis, generalization, forecasting, and document analysis. The resulting model establishes a relationship between the input parameters and the output indicators of the recovery system, characterizing the serviceability of the IWT. In this case, the control parameter is a parameter that characterizes the ratio of the number of samples of military equipment repaired in the 1st-level RVR. Results: the developed model can be used for: analyzing the technical support system of troops; solving optimization problems of managing the technical support of troops: finding the optimal ratio of the number of samples of military equipment repaired by the first and second level RVOS; determining the optimal number of field crews for repairing military equipment while ensuring a given level of serviceability of military equipment and minimizing the cost of repairing military equipment.

Type 1 diabetes mellitus; ovarian reserve; anti-Müllerian hormone; ovarian function

BACKGROUND: Prolonged course of diabetes mellitus often leads to the development of vascular complications, insufficiency of ovarian function. The occurrence of diabetes mellitus in women before pregnancy (pregestational diabetes mellitus) it can have various adverse consequences for the mother, fetus, child and the course of pregnancy. Pregnancy planning in women with pregestational diabetes significantly improves the outcomes of pregnancy and childbirth. AIM: The aim of this study was to analyze gonadotropic and ovarian function parameters in patients with type 1 diabetes mellitus depending on the age of onset, duration and compensation level of the disease. MATERIALS AND METHODS: The patients included into this clinical prospective study were divided into two groups. The main group consisted of 216 patients with type 1 diabetes mellitus aged 18 to 39 years (mean age: 27.1 ± 3.1 years). The control group consisted of 30 healthy women of reproductive age. Chemiluminescent immunoassay was used to determine blood serum levels of anti-Müllerian hormone, follicle-stimulating hormone, luteinizing hormone, prolactin, estradiol, testosterone, free testosterone, and sex hormone-binding globulin from day 2 to day 5 of the menstrual cycle. Serum progesterone levels were measured on days 20–23 of the menstrual cycle for three consecutive cycles. Glycated hemoglobin levels were also studied in the blood serum of patients with type 1 diabetes mellitus. All the patients underwent pelvic ultrasound examination to assess the cohort of antral follicles and ovarian volume. RESULTS: The average age of menarche in patients with type 1 diabetes mellitus who developed the disease at the age of under 10 years was 14.2 ± 1.2 years. This was higher than in the group of girls with the onset of the disease over the age of 10 years (13.5 ± 1.2 years) and in women of the control group (11.9 ± 1.1 years). When assessing the ovarian reserve in patients with type 1 diabetes mellitus, we found a decrease in anti-Müllerian hormone level and antral follicle count in the group of women with disease onset at the age of under 10 years. We did not find differences in the ovarian reserve parameters in patients depending on disease duration. Normogonadotropic normoprolactinemic ovarian insufficiency was detected in 154 (71.3%) of 216 patients, while the rest 62 (28.7%) women had an ovulatory menstrual cycle. In patients with anovulation, luteal phase deficiency and ovulatory menstrual cycle, we found no differences between the age of development of type 1 diabetes mellitus, its duration, glycated hemoglobin levels, total daily insulin dose and insulin dose per kilogram of body mass. In patients receiving intensive insulin therapy with continuous subcutaneous insulin infusion, glycated hemoglobin level was lower than in those receiving multiple dose insulin injection therapy. CONCLUSIONS: The average age of menarche in patients with type 1 diabetes mellitus is higher than in healthy women. The ovarian reserve parameters in patients with early onset of the disease, before 10 years of age, are lower than in patients who developed type 1 diabetes mellitus after 10 years of age. Duration of pregnancy planning period depends on compensation level of the disease and lasts from six to 12 months. This requires the doctor and patient to prepare for the implementation of reproductive tasks as early as possible, especially in patients whose disease onset occurred in pre-pubertal period.

Special Issue on NIED Frontier Research on Science and Technology for Disaster Risk Reduction and Resilience 2024

We are pleased to publish this special issue, dedicated to the NIED Frontier Research on Science and Technology for Disaster Risk Reduction and Resilience 2024. The fifth NIED mid-/long-term plan period began in 2023, and this issue includes the first results of six papers, two reviews, one survey report, one note, and one material. Recently, violent natural disasters have triggered the development of effective countermeasures. Akita, Yamaguchi et al., and Hirashima et al. dealt with climate hazards such as heavy rainfall, snow, and ice disasters. Yamazaki-Honda reported the progress and challenges of disaster reduction and climate change adaptation using DRR strategies. Yadab et al., Akita, and Naito et al. reported data analysis and suggestions to evaluate seismic and volcanic hazards. Nagata et al. proposed the ICT tool “YOU@RISK” to educate regarding volcanic disaster risks. Sato et al. emphasized the importance and effectiveness of information technology. Kimura et al. emphasized preparedness and elaborated on measures to improve preparedness for all natural hazards. These new outcomes will promote the development of a sustainable society against these hazards and will be flagships to proceed with NIED research projects.

"Curriculum-project-supervisor" interactively enhance the innovation capability of postgraduates majoring in bioengineering

According to the Bio-economy Development Plan during the 14th Five-Year Plan period, biotechnology has become an effective force to promote future development. More than 220 universities and research institutes in China have got the right to confer master's degrees in bioengineering. Great attention has been paid to the cultivation of top innovative talents that can serve the innovation-driven development of the national bio-economy. In the last 15 years, the Research Center of Microbial-Manufacturing Engineering in Jiangnan University has built a diversified education platform, recruited high-level faculty members, and innovated the scientific research management. The new concept and method for cultivating the innovation capabilities of postgraduates in a multi-dimension and whole-process manner have been formed, which involved building a curriculum, focusing on major projects, and establishing a supervisor team. This cultivation mode has comprehensively improved the engineering and academic innovation capabilities of postgraduates majoring in bioengineering.

Carbon emissions and drivers across five urban agglomerations of China: Comparison between the 12th and 13th Five-Year Plan periods

Carbon emissions and drivers across five urban agglomerations of China: Comparison between the 12th and 13th Five-Year Plan periods

Fleet repositioning in the tramp ship routing and scheduling problem with bunker optimization: A matheuristic solution approach

This paper investigates an important planning problem faced by dry bulk shipping operators, referred to as the Tramp Ship Routing and Scheduling Problem with Bunker Optimization (TSRSPBO). The problem is to maximize the overall profit of a fleet of vessels by selecting cargoes and determining ship routes and schedules. We consider this problem under a set of practically relevant features such as flexibility in cargo quantities, as well as bunkering decisions on where to procure fuel and how much. As a particularly novel feature, we address the regional allocation of vessels at the end of the planning period to be well prepared for meeting (uncertain) future demand. To incorporate this, we consider the TSRSPBO as a two-stage stochastic programming problem, where cargo selection, routing, and bunkering decisions are solved in the first-stage problem, and the recourse cost of fleet repositioning is considered in the second stage. We present arc flow and path flow formulations, where the latter employs a priori generation of feasible routes as input. For solving realistically sized instances, we propose a matheuristic based on an Adaptive Large Neighborhood Search (ALNS) framework that iteratively generates columns and solves the path flow model. Computational experiments based on real data show that this matheuristic finds high-quality solutions for large test instances with 120 cargoes, 30 vessels, and ten bunker ports in less than one hour. Also, considering the TSRSPBO as a two-stage stochastic problem achieves the highest profits and is solved almost as quickly as the deterministic problem variant.

Integrated risk management and maintenance planning in Oil and Gas Supply Chain operations under market uncertainty

The Oil and Gas Supply Chain (OGSC) is a multifaceted network comprising diverse activities and echelons. Instability or interruptions can cause economic fluctuations, impacting industries, markets, and consumers. Maintenance activities, which pause production but extend facilities' life, are recommended during non-peak demand periods to avoid production losses and meet customer demand. To mitigate these effects, decisions on operations planning, maintenance scheduling, and maintenance team assignments should be optimized in a risk management framework. The proposed model adopts a mixed-integer linear programming (MILP) framework and is solved via a sequential approach that incorporates the relax-and-fix (RF) heuristic in order to find a solution that is close to optimal. Subsequently, the solution serves as an initial solution for the CPLEX solver, which employs a branch-and-cut algorithm to attain the exact optimal solution. The practicality of this model has been showcased through its application to the supply chain in Saudi Arabia. The model efficiently schedules maintenance activities evenly and consistently across the OGSC plants over the planning period to reduce lost sales by keeping plants operational during high-demand periods. Furthermore, a sensitivity analysis was conducted to investigate the influence of the decision-maker's risk attitude on the outcomes that were obtained.

Artificial intelligence empowerment in China’s energy landscape: enhancing power grid investment efficiency

Against the backdrop of China’s initiative to construct a new power system focusing on new energy, optimizing power grid investment holds significant importance. This study aims to investigate whether the application of artificial intelligence (AI) contributes to power grid investment efficiency. By considering diverse factors, power grid investment efficiency in China is assessed by using a Slack-based measure model. Then we analyze the relationship between AI and power grid investment efficiency, as well as their nonlinear threshold effect. We find a notable increase in China’s power grid investment efficiency, accompanied by evident regional differences. In addition, the utilization of AI exerts a significantly positive effect on power grid investment efficiency. Particularly, such a promoting effect is more pronounced in the China Southern Power Grid cohort and remains significant during the 12th Five-Year Plan period. Moreover, grid investment exhibits a double-threshold effect, and it diminishes the contributing effect of AI on power grid investment efficiency. AI shows a single threshold effect on power grid investment efficiency as electricity sales increase, and the positive impact manifests only when electricity sales surpass a specific threshold. These insights are important for the strategic deployment of power grid projects through using AI.

Graph theory-enhanced integrated distribution network reconfiguration and distributed generation planning: A comparative techno-economic and environmental impacts analysis

In today's world, eco-friendly solutions are crucial for efficient power delivery and assessing their corresponding economic and environmental benefits is essential. As innovators, it is also imperative to continually improve on existing techniques to solve a problem. Evaluating the existing literature in this area of study, gaps of improving the optimization techniques by reducing the amount of infeasible configurations the reconfiguration procedure encounters was established, additionally, the need to utilize distributed generations that significantly reduce carbon footprint in the environment was also ascertained. Hence, this paper presents an effective integration method for the simultaneous reconfiguration of Radial Distribution Networks (RDNs) and Photovoltaic (PV) DGs allocation, considering the tripodal issues of cost, operational efficiency, and environmental sustainability. A modification of the adaptive mountain gazelle optimizer (AMGO) enhanced with graph theory is deployed for the optimization procedures. The crucial feature of the proposed approach is the reduction of unfeasible configurations throughout the optimization procedure toward satisfying the network's radiality constraints, achieving consistent convergence and reduced computation time. The technical benefits are active power loss minimization, voltage stability, and voltage profile improvement. The economic benefits are analyzed by estimating the purchased power, the associated cost of power losses, and the cost of DGs and switches over a planning period of 20 years. The consequent environmental benefits are analyzed in detail, highlighting the significant reduction in pollutant emissions. The proposed model was tested on the IEEE 33- and 69-bus RDN, considering several scenarios, including synchronous network reconfiguration and DG installations. From the results procured, the simultaneous network reconfiguration and DG allocation provided better outcomes, yielding minimum active power loss of 35.36 kW, minimum voltage of 0.9541 p.u., voltage stability index of 1.9936 p.u., total planning cost of $3.456 million, and emission of 1.744 million lb/hr, respectively, for the 33-bus systems. The corresponding value for the 69-bus system is 32.57 kW, 0.9832 p.u., 2.3847 p.u., $ 2.524 million, and 2.53 million lb/hr, respectively. The proposed model was compared with other reported techniques for performance validation, and its efficacy and superior performance was established.

Qualitative Evaluation of a Quality Improvement Collaborative Implementation to Improve Acute Ischemic Stroke Treatment in Nova Scotia, Canada.

The Atlantic Canada Together Enhancing Acute Stroke Treatment (ACTEAST) project is a modified quality improvement collaborative (mQIC) designed to improve ischemic stroke treatment rates and efficiency in Atlantic Canada. This study evaluated the implementation of the mQIC in Nova Scotia using qualitative methods. The mQIC spanned 6 months, including two learning sessions, webinars, and a per-site virtual visit. The learning sessions featured presentations about the project and the improvement efforts at some sites. Each session included an action planning period where the participants planned for the implementation efforts over the following 2 to 4 months, called "action periods". Eleven hospitals and Emergency Health Services (EHS) of Nova Scotia participated. The Consolidated Framework for Implementation Research (CFIR) was utilized to develop a semi-structured interview guide to uncover barriers and facilitators to mQIC's implementation. Interviews were conducted with 14 healthcare professionals from 10 entities, generating 458 references coded into 28 CFIR constructs. The interviews started on 17 June 2021, 2 months after the intervention period, and ended on 7 October 2021. Notably, 84% of these references were positively framed as facilitators., highlighting the various aspects of the mQIC and its context that supported successful implementation. These facilitators encompassed factors such as networks and communications, strong leadership engagement, and a collaborative culture. Significant barriers included resource availability, relative priorities, communication challenges, and engaging key stakeholders. Some barriers were prominent during specific phases. The study provides insights into quality improvement initiatives in stroke care, reflecting the generally positive opinions of the interviewees regarding the mQIC. While the quantitative analysis is still ongoing, this study highlights the importance of addressing context-specific barriers and leveraging the identified facilitators for successful implementation.

Carbon-oriented energy system planning using forest carbon sink

More than 130 countries and regions have put forward various climate goals, which makes carbon-oriented energy system planning a heated topic. However, these planning studies do not consider the carbon fixation role played by forest carbon sinks (FCSs). To take advantage of the carbon fixation role of FCSs, this paper will develop a carbon-cycle integrated energy hub (CC-EH) model to quantify the economic advantages of FCSs in planning a zero-carbon energy system, where energy flow and carbon flow are both analyzed. A total planning and operating costs minimization with the constraints of CO2 emissions is proposed as a mixed integer nonlinear programming (MINLP) optimization model and the overall problem is solved based on commercial solver. The proposed model is validated by case studies on six medium to large-size cities in different geographical locations in China. Results indicate that the typical cities in China can fulfill their carbon-neutral commitments by 2060. Throughout the entire planning period, FCSs can offset up to 55.31 % of the total carbon dioxide emissions from urban energy systems. Besides, FCSs achieved by forestation will help the energy system to reduce up to 36 % of the planning cost compared to the case without using FCSs.

Exploration of the Talent Cultivation Model for the Integration of Industry and Education in University Asset Evaluation

During the 14th Five Year Plan period, the main task of talent team construction in China’s asset appraisal industry was to develop innovative talent training models. Therefore, this article focuses on the talent cultivation model of integrating industry and education in asset evaluation in universities, systematically summarizes the theoretical and practical significance of research on asset evaluation talent cultivation models in universities, and explores the construction measures of asset evaluation talent cultivation models based on the integration of industry and education that meet social needs and the development of the times [1]. At the same time, the strategy of constructing a deep integration talent training system was explored, guided by the integration of industry and education, to cultivate asset evaluation composite talents with strong practical skills. The aim is to provide a reference for improving the quality of asset evaluation professionals in China and promoting the development of asset evaluation talent training models.