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学者姓名：黄建华
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Abstract ：
碳交易价格受到宏观经济、能源政策等多种因素的影响,表现出强波动性、非线性等特征,给碳交易价格的准确预测带来巨大困难.针对这一问题,基于二次分解和误差修正策略构建一种碳交易价格预测模型:首先,使用浣熊优化算法优化的变分模态分解方法分解碳价序列,降低原始序列的复杂度;其次,使用经验小波变换对变分模态分解产生的残差序列进行二次分解,充分提取残差序列中的有效信息;然后,使用浣熊优化算法优化的极限学习机对各分量进行预测,获得初始预测结果和误差序列;最后,使用基本和浣熊优化算法优化的极限学习机对误差序列进行分解和预测,并利用误差预测结果对初始预测结果进行修正,得到最终预测结果.选取深圳、湖北和福建 3个碳交易市场的碳价数据进行实证验证,结果表明,所提出的模型相比于其他对照模型具有更优异的预测精度和稳定性,有效提高碳价预测的准确性.
Keyword ：
二次分解 二次分解 极限学习机 极限学习机 浣熊优化算法 浣熊优化算法 碳交易价格 碳交易价格 误差修正 误差修正
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| GB/T 7714 | 何志超 , 黄建华 . 基于二次分解和误差修正的中国碳交易价格预测 [J]. | 科技管理研究 , 2024 , 44 (13) : 200-214 . |
| MLA | 何志超 等. "基于二次分解和误差修正的中国碳交易价格预测" . | 科技管理研究 44 . 13 (2024) : 200-214 . |
| APA | 何志超 , 黄建华 . 基于二次分解和误差修正的中国碳交易价格预测 . | 科技管理研究 , 2024 , 44 (13) , 200-214 . |
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长江集装箱运价指数作为长江航运市场的晴雨指向标，能够有效反映中国长江航运的经济情况，同时侧面反映出中国内河航运的发展动态。通过对长江集装箱运价指数的预测，可以为沿岸航运企业经营决策和政府宏观经济制定提供重要依据。选取影响长江集装箱运价指数的8个指数，运用BP神经网路、RBF神经网络对2017年至2022年5月长江集装箱运价指数进行预测，提出了一种改进的PSO-RBF组合模型，获得的预测误差较小。结果表明：粒子群算法能对RBF神经网络的输出权重、隐单元中心等关键参数取值进行寻优，使其能够更好地收敛，结果优于其他算法；PSO-RBF组合模型是预测长江集装箱运价指数的一种有效方法。
Keyword ：
RBF神经网络 RBF神经网络 粒子群算法 粒子群算法 组合模型 组合模型 长江集装箱运价指数 长江集装箱运价指数 预测 预测
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| GB/T 7714 | 黄建华 , 缪思琪 . 基于PSO-RBF组合模型的长江集装箱运价指数预测 [J]. | 武汉理工大学学报(信息与管理工程版) , 2024 , 46 (02) : 229-236 . |
| MLA | 黄建华 等. "基于PSO-RBF组合模型的长江集装箱运价指数预测" . | 武汉理工大学学报(信息与管理工程版) 46 . 02 (2024) : 229-236 . |
| APA | 黄建华 , 缪思琪 . 基于PSO-RBF组合模型的长江集装箱运价指数预测 . | 武汉理工大学学报(信息与管理工程版) , 2024 , 46 (02) , 229-236 . |
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快递进村具有成本高和效率低的困难，邮政与民营快递企业在共建配送中心、开展共同配送业务等方面进行合作，是解决这一问题的重要手段。因此围绕共建共配的邮快合作模式，分析了邮政快递企业和民营快递企业之间的合作和博弈关系，并构建了演化博弈模型，选取某区的实际数据作为算例，探讨不同因素对合作稳定性的影响以及政府政策在邮快合作中所起的作用效果。结果表明：邮政占据主导地位对推进快递进村具有一定优势，政府推进邮快合作的政策补贴应考虑多种补贴形式。
Keyword ：
共建共配 共建共配 快递进村 快递进村 政府管理 政府管理 演化博弈 演化博弈 邮快合作 邮快合作
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| GB/T 7714 | 黄建华 , 廖梦 . 快递进村倡议下“邮快合作”主体博弈关系研究 [J]. | 武汉理工大学学报(信息与管理工程版) , 2024 , 46 (02) : 253-259,268 . |
| MLA | 黄建华 等. "快递进村倡议下“邮快合作”主体博弈关系研究" . | 武汉理工大学学报(信息与管理工程版) 46 . 02 (2024) : 253-259,268 . |
| APA | 黄建华 , 廖梦 . 快递进村倡议下“邮快合作”主体博弈关系研究 . | 武汉理工大学学报(信息与管理工程版) , 2024 , 46 (02) , 253-259,268 . |
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针对既有玻璃幕墙的安全评价问题，考虑指标信息的不确定性与等级归属的复杂性，提出一种基于模糊熵与灰云聚类模型的既有玻璃幕墙安全评价方法。首先，以实际工程为背景，通过识别既有玻璃幕墙安全风险因素，构建一套定性与定量指标相结合的安全评价指标体系；其次，基于可变模糊云与正态云模型进行评价指标的赋值；再次，运用极差最大化组合赋权法，计算评价指标的权重；最后，引入灰云聚类模型与模糊熵，实现既有玻璃幕墙安全状态的二维评估。实例结果显示：该方法既能对玻璃幕墙的安全状态进行诊断，还能运用模糊熵，从复杂性的层面揭示既有幕墙的健康状况，进而为既有玻璃幕墙的安全评估提供可行思路。
Keyword ：
安全工程 安全工程 安全评价 安全评价 既有玻璃幕墙 既有玻璃幕墙 模糊熵 模糊熵 灰云聚类模型 灰云聚类模型
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| GB/T 7714 | 黄建华 , 张翔 . 模糊熵与灰云模型在既有玻璃幕墙安全评价中的应用 [J]. | 安全与环境学报 , 2024 , 24 (04) : 1275-1283 . |
| MLA | 黄建华 等. "模糊熵与灰云模型在既有玻璃幕墙安全评价中的应用" . | 安全与环境学报 24 . 04 (2024) : 1275-1283 . |
| APA | 黄建华 , 张翔 . 模糊熵与灰云模型在既有玻璃幕墙安全评价中的应用 . | 安全与环境学报 , 2024 , 24 (04) , 1275-1283 . |
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我国长江航运干散货运价指数(YBFI)呈现非线性、非平稳性等波动特征，传统的单一预测模型和组合预测法难以获得较好的预测效果。为此，基于“分解-重构-预测-集成”的思想，提出一种基于变分模态分解(VMD)的YBFI组合预测模型构建方法。选用变分模态分解(VMD)将原始运价指数序列分解为多个模态分量，并通过聚类分析将分量重构为高频、中频、低频和趋势项，对重构后的序列波动特点进行解释。选用BPNN对高频项和低频项进行预测，采用PSO-SVM方法对中频项和趋势项进行预测，最后将重构项预测结果相加集成得到最终预测值。实证结果表明，构建的基于VMD的组合预测模型比SVM、BPNN、ARIMA、PLS等单一预测模型，以及未优化的VMD组合模型、VMD-BP等组合模型具有更好的预测效果。
Keyword ：
变分模态分解 变分模态分解 神经网络 神经网络 粒子群优化算法-支持向量机 粒子群优化算法-支持向量机 组合模型预测 组合模型预测 运价指数 运价指数
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| GB/T 7714 | 黄建华 , 刘睿涵 . 基于VMD的长江航运干散货运价指数预测 [J]. | 武汉理工大学学报(信息与管理工程版) , 2024 , 46 (01) : 53-61 . |
| MLA | 黄建华 等. "基于VMD的长江航运干散货运价指数预测" . | 武汉理工大学学报(信息与管理工程版) 46 . 01 (2024) : 53-61 . |
| APA | 黄建华 , 刘睿涵 . 基于VMD的长江航运干散货运价指数预测 . | 武汉理工大学学报(信息与管理工程版) , 2024 , 46 (01) , 53-61 . |
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The occurrence of safety incidents for existing glass curtain walls (EGCWs) pronounced menace to the security of both lives and property. Undertaking safety assessment for EGCWs carries essential practical significance. However, current fuzzy evaluation methods overlook the uncertainty of indicator weights and the intricacies of rank attribution. In response, this paper proposes a novel approach to the safety assessment of EGCWs. This research establishes a framework of evaluation indicators for EGCWs and divides the safety ranks of each indicator into four tiers: Safe, Mild risk, Moderate risk, and High risk. Quantitative and qualitative indicators are quantified via the variable fuzzy cloud algorithm and cloud model. The information cloud combination weighting method is introduced to determine the weight clouds of indicators. Finally, a two-dimensional assessment result is derived using an improved fuzzy comprehensive evaluation method and fuzzy entropy. The exemplified outcomes demonstrate that this approach captures the safety status of evaluation subjects based on risk ranks, and fuzzy entropy addresses two issues: inconsistent level attribution and the comparison of identical risk ranks. The appraisal method further unveils the safety details of EGCWs, with findings that align consistently with the actual situation.
Keyword ：
cloud model cloud model existing glass curtain wall existing glass curtain wall fuzzy entropy fuzzy entropy Safety evaluation Safety evaluation variable fuzzy cloud algorithm variable fuzzy cloud algorithm
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| GB/T 7714 | Zhang, Xiang , Huang, Jianhua . Safety assessment of existing glass curtain wall based on fuzzy entropy and comprehensive cloud [J]. | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS , 2024 , 46 (2) : 5125-5137 . |
| MLA | Zhang, Xiang 等. "Safety assessment of existing glass curtain wall based on fuzzy entropy and comprehensive cloud" . | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 46 . 2 (2024) : 5125-5137 . |
| APA | Zhang, Xiang , Huang, Jianhua . Safety assessment of existing glass curtain wall based on fuzzy entropy and comprehensive cloud . | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS , 2024 , 46 (2) , 5125-5137 . |
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Selecting suppliers for prefabricated components (PCs) involves a complex decision-making process, frequently relying on ambiguous information and subjective judgment. However, most existing methods use precise values to portray indicator information and overlook the uncertainty of weights and the subjective preferences of decision-makers (DMs). In order to address these limits, this paper proposes a novel approach to select suppliers of PCs. Initially, an evaluation index system for suppliers is established through literature analysis and a questionnaire survey. The system comprises six layers: product quality, price, service level, comprehensive ability, supply ability, and environmental sustainability. The group decision matrix is then constructed using the set-valued statistical method and the prospect theory. The index weights are determined by a combination weighting method. Next, the cobweb model is introduced to analyze the disparity between the alternative and ideal solutions, describing their similarities in terms of area and shape. Lastly, cobweb similarity is employed instead of comprehensive distance, combined with the minimum sum of squares criterion, to improve the closeness algorithm and contrast the alternatives. The results demonstrate that this method facilitates a comprehensive evaluation of the benefits and drawbacks of various alternatives from diverse perspectives. Furthermore, it allows flexible adjustments based on the risk preferences of DMs, ensuring accurate and reliable decision results.
Keyword ：
cobweb model cobweb model cobweb similarity cobweb similarity prospect theory prospect theory risk preference risk preference Select suppliers Select suppliers
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| GB/T 7714 | Zhang, Xiang , Huang, Jianhua , Fang, Liting et al. A supplier selection method based on cobweb similarity and prospect theory for prefabricated components [J]. | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS , 2024 , 46 (2) : 4467-4479 . |
| MLA | Zhang, Xiang et al. "A supplier selection method based on cobweb similarity and prospect theory for prefabricated components" . | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 46 . 2 (2024) : 4467-4479 . |
| APA | Zhang, Xiang , Huang, Jianhua , Fang, Liting , Li, Qian . A supplier selection method based on cobweb similarity and prospect theory for prefabricated components . | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS , 2024 , 46 (2) , 4467-4479 . |
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This paper constructs a tripartite evolutionary game model of government, dealers, and ginger farmers under asymmetric price transmission and explores the impact of the target price insurance on the stabilization strategy of the tripartite evolutionary game. It is also demonstrated that farmers' interests can be effectively protected under long-term government regulation and issuance of reasonable insurance subsidy coefficients. Finally, the model is assigned according to the actual data to systematically reveal the factors affecting the decision of each actor. The research shows that: long-term government regulation is necessary to effectively curb speculation, while the implementation of target price insurance can improve farmers' trading position; the probability of government regulation and implementation is not only related to the cost and social benefits but also influenced by ginger trading volume, while the probability of ginger dealers choosing to hoard speculation increases with the increase of ginger trading volume.
Keyword ：
agricultural products trading agricultural products trading dealers hoarding ginger dealers hoarding ginger government regulation government regulation target price insurance target price insurance tripartite evolutionary game tripartite evolutionary game
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| GB/T 7714 | Huang, Jianhua , Liu, Ruihan , Zhang, Tingting . A tripartite evolutionary game model of ginger transaction under the "regulation plus target price insurance " policy [J]. | INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH , 2023 , 32 (3) : 1792-1815 . |
| MLA | Huang, Jianhua et al. "A tripartite evolutionary game model of ginger transaction under the "regulation plus target price insurance " policy" . | INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 32 . 3 (2023) : 1792-1815 . |
| APA | Huang, Jianhua , Liu, Ruihan , Zhang, Tingting . A tripartite evolutionary game model of ginger transaction under the "regulation plus target price insurance " policy . | INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH , 2023 , 32 (3) , 1792-1815 . |
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针对电动汽车配送过程中耗电速率受荷载大小影响的特点,探讨了动态负载下电动汽车耗电速率和不完全充电策略问题,并以电动车固定费用、行驶费用、电量补充费用和时间窗惩罚费用等综合成本最优为目标,构建了带软时间窗的车辆路径优化模型,设计了改进的混合遗传退火求解算法.最后,以A生鲜企业电动汽车配送业务为例,对模型及算法的有效性进行了验证.结果表明:车辆动态负载情形下,采用不完全充电策略比完全充电策略在充电时间、行驶距离、配送费用等方面具有显著优势;与经典遗传算法相比,所提出的改进混合遗传退火算法能够显著提高收敛速度.
Keyword ：
充电策略 充电策略 动态负载 动态负载 混合遗传退火算法 混合遗传退火算法 电动汽车 电动汽车 车辆路径优化 车辆路径优化
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| GB/T 7714 | 黄建华 , 刘方翔 . 动态负载下电动汽车充电策略及路径优化问题 [J]. | 计算机集成制造系统 , 2023 , 29 (11) : 3909-3921 . |
| MLA | 黄建华 et al. "动态负载下电动汽车充电策略及路径优化问题" . | 计算机集成制造系统 29 . 11 (2023) : 3909-3921 . |
| APA | 黄建华 , 刘方翔 . 动态负载下电动汽车充电策略及路径优化问题 . | 计算机集成制造系统 , 2023 , 29 (11) , 3909-3921 . |
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Accurately forecasting the price of non-ferrous metals is of great significance for traders to avoid risks, enterprises to arrange production plans, and countries to formulate economic policies. In order to improve the forecasting accuracy of non-ferrous metal prices, this paper proposes a novel non-ferrous metal price hybrid forecasting model named IVWAIEE (IVMD-WPD-ARIMA-IELM-ECD). Firstly, the original price series is decomposed into several smoother IMFs using variational mode decomposition (VMD). Simultaneously, the improved sparrow search algorithm (IFASSA) is used to optimize the parameters of VMD to improve the adaptability of VMD. Secondly, wavelet packet decomposition (WPD) is used to decompose the residual sequence generated by VMD to further extract the information in the residual sequence. Then, the components generated by VMD and WPD are defined as high frequency components and low frequency components according to the zero-crossing rate. ARIMA is used to forecast the low frequency components with gentle fluctuations, and extreme learning machine optimized by IFASSA (IELM) is used to forecast the high frequency components with strong fluctuations. The forecasting results of each component are accumulated to obtain the initial forecasting results and error sequence of the non-ferrous metal price. Next, WPD is used to further decompose the error sequence, and the error subsequence is predicted by ARIMA and IELM to obtain the error prediction results. Finally, the error prediction results are used to correct the initial forecasting results, and the final forecasting results of non-ferrous metal prices are obtained. In order to verify the superiority of the proposed model, the copper, aluminum, and zinc futures prices of the London Metal Exchange (LME) are selected as empirical data to verify the model. The results show that the proposed IVWAIEE model has better prediction accuracy and robustness than other benchmark models. Its RMSE values in predicting copper, aluminum, and zinc futures prices are 0.2238, 0.1863, and 0.2137, respectively, and MAE values are 0.1696, 0.1171, and 0.1644, respectively, which are lower than those of other benchmark models; The proposed model not only enriches the application of secondary decomposition and error correction in the field of non-ferrous metal price forecasting, but also solves the problems of insufficient adaptability and underutilization of residual sequence in the traditional variational mode decomposition method; The research results of this paper can provide scientific and effective guidance for the investment, production, and decision-making of non-ferrous metal stakeholders.
Keyword ：
Extreme learning machine Extreme learning machine Non-ferrous metals price forecasting Non-ferrous metals price forecasting Sparrow search algorithm Sparrow search algorithm Variational mode decomposition Variational mode decomposition Wavelet packet decomposition Wavelet packet decomposition
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| GB/T 7714 | He, Zhichao , Huang, Jianhua . A novel non-ferrous metal price hybrid forecasting model based on data preprocessing and error correction [J]. | RESOURCES POLICY , 2023 , 86 . |
| MLA | He, Zhichao et al. "A novel non-ferrous metal price hybrid forecasting model based on data preprocessing and error correction" . | RESOURCES POLICY 86 (2023) . |
| APA | He, Zhichao , Huang, Jianhua . A novel non-ferrous metal price hybrid forecasting model based on data preprocessing and error correction . | RESOURCES POLICY , 2023 , 86 . |
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