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学者姓名：陈可嘉
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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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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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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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To address the challenges posed by uncertain passenger demand and airport capacity in the secondary allocation of arrival and departure slots for autonomously canceled flights, we have developed a grey multi-objective linear programming (MOLP) model. The model represents the uncertainty of passenger demand and airport capacity using interval grey numbers. The objective of the model is to minimize the total delay costs of airlines and the total delay time of passengers. Additionally, it takes into account constraints such as wake vortex separation and runway capacity. Furthermore, to reduce the complexity associated with solving the developed model, we propose an improved transformation method based on the concepts of grey center and width. This method streamlines the transformation process by converting the objective functions into expressions for the center and width. It employs the epsilon-constraint method to transform one of the objective functions into a constraint defined by the center and width, thereby minimizing the impact of constraint relaxation on the results. The results of the case study present value ranges for both non-cancellation and cancellation strategies. Additionally, the validation outcomes of the enhanced transformation method fall within the verification range, thereby confirming the model's effectiveness and the reliability of the transformation method. The model broadens the application scope of grey programming, while the proposed transformation method enhances the theoretical framework of this field.
Keyword ：
Center and width Center and width Flight arrival and departure Flight arrival and departure Flight cancellation Flight cancellation Grey multi-objective model Grey multi-objective model Slot secondary allocation Slot secondary allocation
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| GB/T 7714 | Chen, Kejia , Chen, Zhenkun . A Grey Multi-objective Model for Slot Secondary Allocation of Arrival and Departure Flights under Autonomous Cancellation [J]. | JOURNAL OF GREY SYSTEM , 2024 , 36 (6) . |
| MLA | Chen, Kejia 等. "A Grey Multi-objective Model for Slot Secondary Allocation of Arrival and Departure Flights under Autonomous Cancellation" . | JOURNAL OF GREY SYSTEM 36 . 6 (2024) . |
| APA | Chen, Kejia , Chen, Zhenkun . A Grey Multi-objective Model for Slot Secondary Allocation of Arrival and Departure Flights under Autonomous Cancellation . | JOURNAL OF GREY SYSTEM , 2024 , 36 (6) . |
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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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针对滨海新城在福州新区规划中的重要地位,文章明确滨海新城与福州新区联动发展的特征,建立滨海新城与福州新区联动发展的系统动力学模型,并借助Vensim软件进行模型检验,选择信息港科技研发系数、投资贡献度、GDP增加系数等作为控制变量进行仿真,结果显示:为了推动滨海新城与福州新区的联动发展,需要加大滨海新城科技研发的投入,重点发展大数据相关产业,同时稳步推进海港、空港、陆港的投资,提升海港、空港、陆港吞吐能力.
Keyword ：
滨海新城 滨海新城 福州新区 福州新区 系统动力学 系统动力学 联动发展 联动发展
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| GB/T 7714 | 陈可嘉 , 吴芊芊 , 傅晟昱 . 滨海新城与福州新区联动发展的系统动力学建模与仿真 [J]. | 现代城市研究 , 2024 , (6) : 93-99 . |
| MLA | 陈可嘉 等. "滨海新城与福州新区联动发展的系统动力学建模与仿真" . | 现代城市研究 6 (2024) : 93-99 . |
| APA | 陈可嘉 , 吴芊芊 , 傅晟昱 . 滨海新城与福州新区联动发展的系统动力学建模与仿真 . | 现代城市研究 , 2024 , (6) , 93-99 . |
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为解决因突发事件产生的航空公司航班中断问题,对中断的离港航班进行恢复,构建最小化航空公司总延误成本和最小化乘客总延误时间的双目标优化模型,设计基于支配强度的自适应非支配排序遗传算法(ANSGA2-DS).提出3种改进操作:快速支配排序方法、新的拥挤距离和自适应精英保留策略.通过福州长乐国际机场某航空公司的运行数据对所提算法进行验证,实验结果表明:与传统的先规划先服务方法相比,所提算法得到的解有大幅优化;与ε约束法相比,所提算法的求解时间总体上低于ε约束法,且求解结果接近ε约束法所得最优结果;与NSGA2、MOEAD等多目标优化算法相比,所提算法表现出更优的性能,能够有效且高效地解决问题,为航空公司达成优化的解决方案提供基础.
Keyword ：
中断航班恢复 中断航班恢复 双目标优化 双目标优化 多目标遗传算法 多目标遗传算法 离港航班 离港航班 航空运输 航空运输
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| GB/T 7714 | 陈可嘉 , 吴钧涛 . 中断离港航班恢复的改进NSGA2算法 [J]. | 北京航空航天大学学报 , 2024 , 50 (6) : 1784-1793 . |
| MLA | 陈可嘉 等. "中断离港航班恢复的改进NSGA2算法" . | 北京航空航天大学学报 50 . 6 (2024) : 1784-1793 . |
| APA | 陈可嘉 , 吴钧涛 . 中断离港航班恢复的改进NSGA2算法 . | 北京航空航天大学学报 , 2024 , 50 (6) , 1784-1793 . |
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多数基于深度学习的情感分类方法过于追求数据驱动,忽视了文本情感特征对于情感分类的影响;而一些融合情感特征的情感分类方法仅利用了部分相关特征,使得其他情感特征并没有得到充分利用.针对这一现象,提出了一种融合词级特征和句级特征的在线评论情感分类模型.首先利用构建的情感元素词典获取情感词、否定词等多种特征词,然后通过多维特征向量表示将多种文本特征转化为词级特征向量和句级特征向量,最后将这些特征向量融入LSTM网络模型完成情感分类,整个模型简称为 MF-LSTM(sentiment classification model based on multidimensional features and LSTM).MF-LSTM 充分利用 了评论文本的情感先验知识,情感分类能力得到显著提升.在3个中文评论数据集上的实验结果表明MF-LSTM模型相比其他深度学习方法具有更好的分类效果,并且在样本数据不平衡的情况下也能具有较好的鲁棒性.
Keyword ：
多特征 多特征 情感分类 情感分类 情感词典 情感词典 深度学习 深度学习 长短时记忆神经网络 长短时记忆神经网络
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| GB/T 7714 | 陈可嘉 , 柯永诚 . 融合多特征的在线评论情感分类 [J]. | 小型微型计算机系统 , 2024 , 45 (5) : 1054-1061 . |
| MLA | 陈可嘉 等. "融合多特征的在线评论情感分类" . | 小型微型计算机系统 45 . 5 (2024) : 1054-1061 . |
| APA | 陈可嘉 , 柯永诚 . 融合多特征的在线评论情感分类 . | 小型微型计算机系统 , 2024 , 45 (5) , 1054-1061 . |
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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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