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学者姓名：陈可嘉
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Abstract ：
数字文化产业赋能乡村振兴的同时,乡村振兴也可以促进数字文化产业的发展.通过构建数字经济和文化产业的评价指标体系,并运用耦合协调度模型,文章对各地区的数字文化产业发展进行了系统评估.同时,构建乡村振兴评价指标体系,采用面板数据分析方法,深入分析了乡村振兴对数字文化产业发展的影响机制.研究结果显示,福建省数字文化产业总体呈上升趋势.面板数据分析表明,乡村振兴显著促进了数字文化产业的发展,通过提升农村消费水平、扩大市场规模和丰富应用场景,为数字文化产业提供了有力支持.此外,基础设施水平、人才与创新水平、文化资源水平在乡村振兴与数字文化产业发展之间发挥了显著的中介效应.
Keyword ：
乡村振兴 乡村振兴 实证分析 实证分析 数字文化产业 数字文化产业 福建省 福建省 面板数据分析 面板数据分析
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| GB/T 7714 | 林鸿熙 , 司徒腾宽 , 陈可嘉 . 乡村振兴战略驱动下福建省地级市数字文化产业发展研究 [J]. | 数学的实践与认识 , 2025 , 55 (3) : 117-130 . |
| MLA | 林鸿熙 等. "乡村振兴战略驱动下福建省地级市数字文化产业发展研究" . | 数学的实践与认识 55 . 3 (2025) : 117-130 . |
| APA | 林鸿熙 , 司徒腾宽 , 陈可嘉 . 乡村振兴战略驱动下福建省地级市数字文化产业发展研究 . | 数学的实践与认识 , 2025 , 55 (3) , 117-130 . |
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对枢纽机场中航班波运行模式下的时隙二次分配问题进行协同决策，能够有效地提高机场的运行效率并降低航班延误所造成的航空公司及旅客的成本损失。本文首先以旅客总延误成本最小化作为效率性目标，引入经济学中的基尼系数作为公平性目标，构建双目标时隙二次分配模型。其次，设计改进的非支配排序遗传算法(NSGA-II)获得Pareto解集，其中引入重复个体控制策略及邻域搜索策略来增强算法的寻优性能。最后，以某枢纽机场的航班运行数据作为算例，实验证明改进的NSGA-II算法在解的个数和质量上明显更优。该研究结果可以为航空公司减少航班延误提供理论和技术支持。
Keyword ：
协同决策 协同决策 多目标优化 多目标优化 改进非支配排序遗传算法 改进非支配排序遗传算法 时隙二次分配 时隙二次分配 航班波 航班波
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| GB/T 7714 | 陈可嘉 , 陈锦涛 . 航班波运行下多目标时隙二次分配的改进NSGA-Ⅱ算法 [J]. | 运筹与管理 , 2025 , 34 (03) : 23-29 . |
| MLA | 陈可嘉 等. "航班波运行下多目标时隙二次分配的改进NSGA-Ⅱ算法" . | 运筹与管理 34 . 03 (2025) : 23-29 . |
| APA | 陈可嘉 , 陈锦涛 . 航班波运行下多目标时隙二次分配的改进NSGA-Ⅱ算法 . | 运筹与管理 , 2025 , 34 (03) , 23-29 . |
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The Aircraft Sequencing Problem (ASP) is a problem that seeks to minimize adverse impacts such as flight delays by adjusting flight sequencing schemes. With the increase in aviation demand, ASP has been garnered more attention in recent years. However, existing ASPs typically assume that the relationships between runways are either entirely independent or entirely interdependent, without considering the complex scenarios where runways have both dependent and independent relationships. Moreover, existing ASP research focusing on multi-objective aspects is relatively scarce, while it is essential to consider multifaceted needs in reality. Therefore, we have established a multi-objective mathematical model for the Aircraft Sequencing Problem with Complex Interdependent Runways (ASP-CIR), aiming to minimize the total delays and makespan. Different from the common lack of problem-specific structural design in existing ASP algorithms, or the need to improve structural strategies, we propose an Improved Multi-Objective Restart Variable Neighborhood Search (IMORVNS) algorithm based on the characteristic of the studied ASP-CIR. In the IMORVNS, we have designed several problem-specific structures guided by constraints, such as initialization and neighborhood search. We tested our new method on 30 different problem instances of three sizes and found it worked better than other recent algorithms. Moreover, a sensitivity analysis on the scenario featuring both interdependent and independent runway relationships was conducted, reaffirming the importance of considering the ASP-CIR scenario.
Keyword ：
Aircraft Sequencing Problem Aircraft Sequencing Problem Complex Interdependent Runways Complex Interdependent Runways Constrained Position Shifting Constrained Position Shifting Variable Neighborhood Search Variable Neighborhood Search
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| GB/T 7714 | Chen, Kejia , Situ, Tengkuan , Fang, Yunfei . An improved multi-objective restart variable neighborhood search algorithm for aircraft sequencing problem with complex interdependent runways [J]. | JOURNAL OF AIR TRANSPORT MANAGEMENT , 2025 , 127 . |
| MLA | Chen, Kejia 等. "An improved multi-objective restart variable neighborhood search algorithm for aircraft sequencing problem with complex interdependent runways" . | JOURNAL OF AIR TRANSPORT MANAGEMENT 127 (2025) . |
| APA | Chen, Kejia , Situ, Tengkuan , Fang, Yunfei . An improved multi-objective restart variable neighborhood search algorithm for aircraft sequencing problem with complex interdependent runways . | JOURNAL OF AIR TRANSPORT MANAGEMENT , 2025 , 127 . |
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为解决航空公司自主取消航班下的进离场时隙二次分配问题,兼顾航空公司和旅客的诉求,本文以航空公司总延误成本和旅客总延误时间最小为目标,建立双目标优化模型.引入参数λ权衡进离场航班延误成本函数的差异,并在约束中区分不同机型航班的周转时间.针对模型特点,采用实数编码,取消航班对应的基因位置返回-1,并在遗传操作中引入学习机制,对支配个体和非支配个体设计不同的交叉变异概率,对精英个体引入Q-learning驱动的通用变邻域搜索策略.3组算例的实验结果表明,改进算法的求解时间分别为29.34,58.61,125.21 s,求解方案分别有9,8,8个.相较于先到先服务方法,航空公司总延误成本分别减少了14.85%、8.47%和9.18%,旅客总延误时间分别减少了1.03%、5.31%和4.68%.相比不取消策略,取消策略下航空公司总延误成本分别减少7.04%、9.38%和11.96%,旅客总延误时间分别增加0.95%、1.21%和1.70%.本文建立的双目标优化模型和提出的改进算法能够降低航空公司延误成本,同时兼顾旅客利益,为自主取消航班下进离场时隙二次分配提供决策支持.
Keyword ：
Q-learning Q-learning 改进NSGA-Ⅱ 改进NSGA-Ⅱ 自主取消航班 自主取消航班 航空运输 航空运输 进离场时隙二次分配 进离场时隙二次分配
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| GB/T 7714 | 陈振坤 , 陈可嘉 . 自主取消航班下进离场时隙二次分配的双目标优化 [J]. | 交通运输系统工程与信息 , 2025 , 25 (3) : 321-334 . |
| MLA | 陈振坤 等. "自主取消航班下进离场时隙二次分配的双目标优化" . | 交通运输系统工程与信息 25 . 3 (2025) : 321-334 . |
| APA | 陈振坤 , 陈可嘉 . 自主取消航班下进离场时隙二次分配的双目标优化 . | 交通运输系统工程与信息 , 2025 , 25 (3) , 321-334 . |
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Flight rescheduling problems have received considerable attention in recent decades, but most studies have neglected the role of airline decision-making and passenger satisfaction, which greatly affects airline competitiveness. In this paper, an airline-driven arrival flight rescheduling problem considering passenger satisfaction is investigated when a ground delay program (GDP) is issued. An improved NSGA-II (iNSGA-II) is tailored to solve the proposed bi-objective model, aiming to minimize the total relevant cost and maximize passenger satisfaction, where passenger satisfaction is portrayed using Prospect Theory. As the model considers multiple recovery strategies, a chromosome coding method is designed, and population initialization, crossover, and mutation are tailored to match the problem characteristics. Additionally, the de-duplication strategy, probability selection, and perturbation strategy are introduced to enhance the algorithm's developmental capabilities. The external archive is also implemented to maintain population diversity. The optimal key parameters used in iNSGA-II are obtained by the Taguchi method. The experimental results prove that the solution of iNSGA-II outperforms the traditional first-come-first-served (FCFS) and can find a reasonable solution set close to the & varepsilon;\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\epsilon $$\end{document}-constraint method in less time. Meanwhile, it is verified that iNSGA-II has better performance and is more conducive to finding the global better Pareto fronts by comparing with NSGA-II, MOEA/D, and MOPSO, which can better provide the basis for the airline's preference decision. Finally, management insights are given by analyzing solutions and the distribution of objective values. The research can offer theoretical insights and practical guidance to assist airlines in rescheduling flights.
Keyword ：
Airline operations Airline operations Flight rescheduling Flight rescheduling Multi-objective optimization Multi-objective optimization NSGA-II NSGA-II Satisfaction Satisfaction
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| GB/T 7714 | Chen, Kejia , Wang, Hongjun . Airline-Driven Arrival Flight Rescheduling Problem Considering Passenger Satisfaction Using Improved NSGA-II [J]. | ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING , 2025 . |
| MLA | Chen, Kejia 等. "Airline-Driven Arrival Flight Rescheduling Problem Considering Passenger Satisfaction Using Improved NSGA-II" . | ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING (2025) . |
| APA | Chen, Kejia , Wang, Hongjun . Airline-Driven Arrival Flight Rescheduling Problem Considering Passenger Satisfaction Using Improved NSGA-II . | ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING , 2025 . |
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为适应协同决策需要,考虑空管部门、航空公司和机场三方诉求,研究了因机场容量下降导致航班延误并违反机场宵禁的航班恢复问题.综合考虑航空公司和旅客利益,提出以航空公司总延误成本最低和旅客总延误时间最少的多目标协同时隙二次分配模型.结合某机场的航班延误数据,求解并验证所提模型的可行性和有效性,并作灵敏度分析.结果表明,本研究建立的多目标航班恢复模型能够在资源优化和任务调度方面更为高效,特别是缓解重型机和中型机的延误时间;在机场容量受限情况下时隙使用分配结果优化超过 26%,有效减少宵禁对航班正常运行的影响,可为航空公司进行时隙二次分配提供科学合理的理论依据.
Keyword ：
多目标规划 多目标规划 时隙二次分配 时隙二次分配 机场宵禁 机场宵禁 灵敏度分析 灵敏度分析 航班恢复 航班恢复
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| GB/T 7714 | 陈可嘉 , 陈梦曦 , 郭小清 . 带宵禁限制的多目标协同时隙二次分配模型 [J]. | 工业工程 , 2025 , 28 (2) : 12-19 . |
| MLA | 陈可嘉 等. "带宵禁限制的多目标协同时隙二次分配模型" . | 工业工程 28 . 2 (2025) : 12-19 . |
| APA | 陈可嘉 , 陈梦曦 , 郭小清 . 带宵禁限制的多目标协同时隙二次分配模型 . | 工业工程 , 2025 , 28 (2) , 12-19 . |
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The paper explores the flight recovery problem of flight delay and violation of airport curfew due to the decline of airport capacity under the collaborative decision making. A multi-objective collaborative slot secondary allocation model is proposed to minimise the total delay cost of airlines and the total delay time of passengers. Three multi-objective decision-making (MODM) techniques are introduced, and the displaced ideal solution (DIS) method is used to select the optimal solution technique. The results show that the weighting method (WM) can generate high-quality solutions in the test data set. Finally, combined with the delayed flight data of an airport, LINGO software is used to solve the model, the sensitivity and the complexity is analysed. The results show that the collaborative scheduling strategy proposed in this paper can provide airlines with scientific and reasonable slot secondary allocation scheme under the condition of limited airport capacity. Copyright © 2024 Inderscience Enterprises Ltd.
Keyword ：
Airports Airports Air traffic control Air traffic control Air transportation Air transportation Decision making Decision making Multiobjective optimization Multiobjective optimization Statistical tests Statistical tests
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| GB/T 7714 | Chen, Kejia , Guo, Xiaoqing , Wang, Haiyan . Multi-objective collaborative slot secondary allocation model with curfew restriction [J]. | International Journal of Industrial and Systems Engineering , 2024 , 47 (3) : 311-333 . |
| MLA | Chen, Kejia 等. "Multi-objective collaborative slot secondary allocation model with curfew restriction" . | International Journal of Industrial and Systems Engineering 47 . 3 (2024) : 311-333 . |
| APA | Chen, Kejia , Guo, Xiaoqing , Wang, Haiyan . Multi-objective collaborative slot secondary allocation model with curfew restriction . | International Journal of Industrial and Systems Engineering , 2024 , 47 (3) , 311-333 . |
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To solve the problem of airline flight disruption caused by emergencies, this paper recovers the disrupted departure flight. A bi-objective optimization model for minimizing airline delay cost and passenger delay time is constructed. An adaptive non-dominated sorting genetic algorithm-Ⅱ based on dominant strengths (ANSGA2-DS) is designed. The novel crowding distance, the adaptive elitist retention technique, and the quick dominant sorting approach are the three enhanced operations that are given. The proposed algorithm is verified by the operation data of an airline in Fuzhou Changle International Airport. The experimental results reveal that, compared with the traditional first scheduling first serve method, the algorithm proposed in this paper can reduce the costs greatly. In contrast to the Ε-constraint approach, the Ε-constrained approach requires a longer solution time, and the resulting solution results are similar to those of the Ε-constrained approach. Compared with the NSAG2 algorithm and the MOEAD algorithm, the algorithm proposed in this paper shows better performance. The proposed algorithm can solve the problem effectively and efficiently, and provide a basis for airlines to reach an optimized solution. © 2024 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.
Keyword ：
Air transportation Air transportation Genetic algorithms Genetic algorithms Sorting Sorting
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| GB/T 7714 | Chen, Kejia , Wu, Juntao . Improved NSGA2 algorithm for disrupted departure flights recovery [J]. | Journal of Beijing University of Aeronautics and Astronautics , 2024 , 50 (6) : 1784-1793 . |
| MLA | Chen, Kejia 等. "Improved NSGA2 algorithm for disrupted departure flights recovery" . | Journal of Beijing University of Aeronautics and Astronautics 50 . 6 (2024) : 1784-1793 . |
| APA | Chen, Kejia , Wu, Juntao . Improved NSGA2 algorithm for disrupted departure flights recovery . | Journal of Beijing University of Aeronautics and Astronautics , 2024 , 50 (6) , 1784-1793 . |
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In view of the lack of interactive information between aspect words and the context in most aspect-level sentiment studies, and the inability to make full use of semantic information. To address the problems above, a model based on self-attention and graph convolution network is proposed. In order to improve the semantic representation ability of the model, the multi-head self-attention mechanism is used to obtain the long-distance dependency relationship of the text, combined with the dependency type matrix. Then, the weight matrix that combines the location information and the relationship type information is calculated and is inputted to the graph convolution network to obtain the text feature representation. Besides, the text aspect attention layer is employed to extract the context-sensitive aspect features, and it is inputted to graph convolution network to obtain aspect feature representation. Finally, the two vectors above are connected to complete the task of sentiment analysis. Simulation results show that the overall performance of the proposed model is better than that these of other comparison models in two open datasets. © 2024 Beijing University of Posts and Telecommunications. All rights reserved.
Keyword ：
Convolution Convolution Semantics Semantics Semantic Web Semantic Web Sentiment analysis Sentiment analysis
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| GB/T 7714 | Chen, Kejia , Huang, Chunxiang , Lin, Hongxi . Aspect-Level Sentiment Analysis Based on Self-Attention and Graph Convolutional Network [J]. | Journal of Beijing University of Posts and Telecommunications , 2024 , 47 (1) : 127-132 . |
| MLA | Chen, Kejia 等. "Aspect-Level Sentiment Analysis Based on Self-Attention and Graph Convolutional Network" . | Journal of Beijing University of Posts and Telecommunications 47 . 1 (2024) : 127-132 . |
| APA | Chen, Kejia , Huang, Chunxiang , Lin, Hongxi . Aspect-Level Sentiment Analysis Based on Self-Attention and Graph Convolutional Network . | Journal of Beijing University of Posts and Telecommunications , 2024 , 47 (1) , 127-132 . |
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With the development of e-shopping, a list of similar products can be found with a large volume of valuable customer reviews online. However, it is generally difficult to compare various aspects of similar products effectively by understanding all relevant online opinions. To help consumers, in this study, how products are ranked according to online reviews is investigated. Firstly, an SC-LDA (Seed Constraint-Latent Dirichlet Allocation) model, which is an extension of the classical topic model LDA (Latent Dirichlet Allocation), is proposed to extract product features. The must-link and cannot-link seed constraints are invited to estimate the probability expansion/reduction value. They help to affect the topic allocation by additional constraints in Gibbs sampling for a higher accuracy on feature extraction. Secondly, an improved convolutional memory neural network model is devised to analyze the sentiment polarity. It takes the advantages of CNN (convolutional neural network) and Bi-LSTM (bidirectional Long Short-Term Memory) and performs dynamic pooling in CNN to prevent the loss of important features. Besides, the concept of group satisfaction degree is introduced, which makes products be compared according to the Regret Theory. It ranks products without a commonly applied reference point and take consumer psychology into considerations. Finally, in the case study, an illustrative example is presented to evaluate the proposed framework. Categories of experiments show that the proposed framework provides consumers with effective purchase suggestions. Code metadata: Permanent link to reproducible Capsule: https://doi.org/10.24433/CO.6445683.v1 and https://d oi.org/10.24433/CO.2658577.v1.
Keyword ：
Group satisfaction Group satisfaction Online opinions Online opinions Product ranking Product ranking Purchase suggestions Purchase suggestions Regret theory Regret theory
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| GB/T 7714 | Chen, Kejia , Zheng, Jingjing , Jin, Jian . Ranking products through online opinions: A text analysis and regret theory-based approach [J]. | APPLIED SOFT COMPUTING , 2024 , 158 . |
| MLA | Chen, Kejia 等. "Ranking products through online opinions: A text analysis and regret theory-based approach" . | APPLIED SOFT COMPUTING 158 (2024) . |
| APA | Chen, Kejia , Zheng, Jingjing , Jin, Jian . Ranking products through online opinions: A text analysis and regret theory-based approach . | APPLIED SOFT COMPUTING , 2024 , 158 . |
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