المؤلفون: 徐世昌, 程刚, 袁敦鹏, 孙旭, 金祖进, 李勇

المصدر: Gong-kuang zidonghua, Vol 48, Iss 9, Pp 8-15, 24 (2022)

مصطلحات موضوعية: 带式输送机, 输送带跑偏监测, 跑偏趋势预测, 堆煤监测, 线激光双目相机, 三维点云, Mining engineering. Metallurgy, TN1-997

Relation: https://doaj.org/toc/1671-251X; https://doaj.org/article/2c3768fadfe64bc2be4add2694f99559

الاتاحة: https://doi.org/10.13272/j.issn.1671-251x.17948
https://doaj.org/article/2c3768fadfe64bc2be4add2694f99559

المؤلفون: 吴兆法, 吴响, 钱建生

المصدر: Gong-kuang zidonghua, Vol 40, Iss 12, Pp 31-36 (2014)

مصطلحات موضوعية: 瓦斯浓度趋势预测, 插值梯形模糊信息粒化, 时间序列, 粒化评价, 加权, Mining engineering. Metallurgy, TN1-997

Relation: https://doaj.org/toc/1671-251X; https://doaj.org/article/6020aa4d6cd043f9b72e5556cddc9509

الاتاحة: https://doi.org/10.13272/j.issn.1671-251x.2014.12.009
https://doaj.org/article/6020aa4d6cd043f9b72e5556cddc9509

المؤلفون: 张海军, 胡晨骏, 凡娜

المصدر: Gong-kuang zidonghua, Vol 40, Iss 10, Pp 72-74 (2014)

مصطلحات موضوعية: 选煤厂, 设备运行状态, 综合评判, 趋势预测, 检修对策, Mining engineering. Metallurgy, TN1-997

Relation: https://doaj.org/toc/1671-251X; https://doaj.org/article/4961935acb7b4795834017f6f941175f

الاتاحة: https://doi.org/10.13272/j.issn.1671-251x.2014.10.019
https://doaj.org/article/4961935acb7b4795834017f6f941175f

المؤلفون: 程曦

مصطلحات موضوعية: 资产管理, 强化学习, 图神经网络, 算法交易, 趋势预测, 计算机科学技术

Relation: http://ir.ia.ac.cn/handle/173211/57103

الاتاحة: http://ir.ia.ac.cn/handle/173211/57103

المؤلفون: 孙志成, 曾鹏, 翟畅

مصطلحات موضوعية: 人工智能, 智慧工厂, 机械设备, 趋势预测

Relation: 仪器仪表标准化与计量; http://ir.sia.cn/handle/173321/27552

الاتاحة: http://ir.sia.cn/handle/173321/27552

المؤلفون: 岳丽欣, 刘自强, 胡正银

مصطلحات موضوعية: 趋势预测, Word2vec模型, 主题演化, 热点主题, Arima模型

Relation: 数据分析与知识发现; http://ir.las.ac.cn/handle/12502/11420

الاتاحة: http://ir.las.ac.cn/handle/12502/11420

المؤلفون: 许浩楠

مصطلحات موضوعية: 量化投资, 深度学习, 股票趋势预测

Relation: http://ir.ia.ac.cn/handle/173211/51948

الاتاحة: http://ir.ia.ac.cn/handle/173211/51948

المؤلفون: 别敦荣, 易梦春

مصطلحات موضوعية: 世界高等教育, 普及化, 趋势预测, 战略选择

Relation: 中国高教研究,2018,(01):57-63; https://dspace.xmu.edu.cn/handle/2288/173902

الاتاحة: https://doi.org/10.16298/j.cnki.1004-3667.2018.01.11
https://dspace.xmu.edu.cn/handle/2288/173902

المؤلفون: 许茜, 李奇, 陈懂懂, 罗彩云, 赵新全, 赵亮

مصطلحات موضوعية: 土地利用/土地覆被变化, CA-Markov模型, 趋势预测, 供需平衡, 利用类型, 三江源

Relation: 干旱区研究; http://210.75.249.4/handle/363003/13712

الاتاحة: http://210.75.249.4/handle/363003/13712

المؤلفون: 潘柱廷, 程学旗, 袁晓如, 周涛, 靳小龙

المساهمون: 启明星辰, 中国计算机学会(CCF), 中国互联网协会, 云安全联盟CSA中国区, 中国科学院计算技术研究所, 中国科学院网络数据科学与技术重点实验室, CCF大数据专家委员会, 北京大学, 北京大学信息科学技术学院, 北京启明星辰信息安全技术有限公司, 中国科学院网络数据科学与技术重点实验室网络数据科学研究部

المصدر: 知网

مصطلحات موضوعية: CCF, 中国计算机学会, 第二年, 发展趋势预测, 可视化方法, 产业发展报告, 应用领域, 隐私保护, 开源技术, 产业生态

Relation: 大数据. 2016, 105-113.; 1929242; http://hdl.handle.net/20.500.11897/480881

الاتاحة: https://hdl.handle.net/20.500.11897/480881

المؤلفون: 张景霓, 苏丹

المساهمون: 广西民族大学文学院, 广西财经学院会计与审计学院分团委

مصطلحات موضوعية: 三江侗族, 侗语使用, 演变趋势预测

Relation: 广西民族大学学报(哲学社会科学版),2016,38(02):191-196; http://ir.calis.edu.cn/hdl/530500/19941

الاتاحة: http://ir.calis.edu.cn/hdl/530500/19941

المؤلفون: 周家民, Zhou, Jia-Min

المساهمون: 蔡炎龍, Tsai, Yen-Lung

مصطلحات موضوعية: 深度學習, 神經網路, 卷積神經網路, 長短期記憶, 股票趨勢預測, 市場模擬, Deep Learning, NN, CNN, LSTM, Stock Trend Forecast, Market Simulation

وصف الملف: 1067705 bytes; application/pdf

Relation: [1] Kunihiko Fukushima and Sei Miyake. Neocognitron: A self-organizing neural network model for a mechanism of visual pattern recognition. In Competition and cooperation in\nneural nets, pages 267–285. Springer, 1982.\n[2] Geoffrey E Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, and Ruslan RSalakhutdinov. Improving neural networks by preventing co-adaptation of feature detectors.\narXiv preprint arXiv:1207.0580, 2012.\n[3] David H Hubel. Single unit activity in striate cortex of unrestrained cats. The Journal of physiology, 147(2):226, 1959.\n[4] David H Hubel and Torsten N Wiesel. Receptive fields of single neurones in the cat’s striate cortex. The Journal of physiology, 148(3):574, 1959.\n[5] WS McCullock and W Pitts. A logical calculus of ideas immanent in nervous activity. archive copy of 27 november 2007 on wayback machine. Avtomaty [Automated Devices] Moscow, Inostr. Lit. publ, pages 363–384, 1956.\n[6] David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George Van Den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc\nLanctot, et al. Mastering the game of go with deep neural networks and tree search. nature, 529(7587):484–489, 2016.\n[7] Bing Xu, Naiyan Wang, Tianqi Chen, and Mu Li. Empirical evaluation of rectified activations in convolutional network. arXiv preprint arXiv:1505.00853, 2015.; G0108751018; https://nccur.lib.nccu.edu.tw//handle/140.119/141180; https://nccur.lib.nccu.edu.tw/bitstream/140.119/141180/1/101801.pdf

الاتاحة: https://nccur.lib.nccu.edu.tw//handle/140.119/141180
https://doi.org/10.6814/NCCU202200774
https://nccur.lib.nccu.edu.tw/bitstream/140.119/141180/1/101801.pdf

المؤلفون: 商肯豪, Shang, Ken-Hao

المساهمون: 蔡瑞煌 林怡伶, Tsaih, Rua-Huan Lin, Yi-Ling

مصطلحات موضوعية: 銅採購議題, 混合學習型決策支援系統, 單隱藏層前饋神經網路, 趨勢預測, copper procurement issue, decision support system, single-hidden layer feedforward neural network, trend forecasting

وصف الملف: 2753246 bytes; application/pdf

Relation: Aamodt, A., and Plaza, E. 1994. "Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches," AI communications (7:1), pp. 39-59.\nAngehrn, A. A., and Lüthi, H.-J. 1990. "Intelligent Decision Support Systems: A Visual Interactive Approach," Interfaces (20:6), pp. 17-28.\nAstudillo, G., Carrasco, R., Fernández-Campusano, C., and Chacón, M. 2020. "Copper Price Prediction Using Support Vector Regression Technique," Applied Sciences (10:19), p. 6648.\nAu, K., Wong, W. K., and Zeng, X. 2006. "Decision Model for Country Site Selection of Overseas Clothing Plants," The International Journal of Advanced Manufacturing Technology (29:3), pp. 408-417.\nBabu, C. N., and Reddy, B. E. 2014. "A Moving-Average Filter Based Hybrid Arima–Ann Model for Forecasting Time Series Data," Applied Soft Computing (23), pp. 27-38.\nBanjac, G., Vašak, M., and Baotić, M. 2015. "Adaptable Urban Water Demand Prediction System," Water Science and Technology: Water Supply (15:5), pp. 958-964.\nBarros, L. Y., Poletto, J. C., Neis, P. D., Ferreira, N. F., and Pereira, C. H. 2019. "Influence of Copper on Automotive Brake Performance," Wear (426), pp. 741-749.\nBelz, R., and Mertens, P. 1996. "Combining Knowledge-Based Systems and Simulation to Solve Rescheduling Problems," Decision Support Systems (17:2), pp. 141-157.\nBenardos, P., and Vosniakos, G.-C. 2007. "Optimizing Feedforward Artificial Neural Network Architecture," Engineering applications of artificial intelligence (20:3), pp. 365-382.\nBengio, Y. 2012. "Practical Recommendations for Gradient-Based Training of Deep Architectures," in Neural Networks: Tricks of the Trade. Springer, pp. 437-478.\nBergerson, K., and Wunsch, D. C. 1991. "A Commodity Trading Model Based on a Neural Network-Expert System Hybrid," Ijcnn-91-seattle international joint conference on neural networks: IEEE, pp. 289-293.\nBerson, A., and Thearling, K. 1999. Building Data Mining Applications for Crm. McGraw-Hill, Inc.\nBonczek, R. H., Holsapple, C. W., and Whinston, A. B. 2014. Foundations of Decision Support Systems. Academic Press.\nÇelik, U., and Başarır, Ç. 2017. "The Prediction of Precious Metal Prices Via Artificial Neural Network by Using Rapidminer," Alphanumeric Journal (5:1), pp. 45-54.\nCharlot, P., and Marimoutou, V. 2014. "On the Relationship between the Prices of Oil and the Precious Metals: Revisiting with a Multivariate Regime-Switching Decision Tree," Energy Economics (44), pp. 456-467.\nChi, R. H., and Kiang, M. Y. 1991. "An Integrated Approach of Rule-Based and Case-Based Reasoning for Decision Support," Proceedings of the 19th annual conference on Computer Science, pp. 255-267.\nChirodea, M. C., Novac, O. C., Novac, C. M., Bizon, N., Oproescu, M., and Gordan, C. E. 2021. "Comparison of Tensorflow and Pytorch in Convolutional Neural Network-Based Applications," 2021 13th International Conference on Electronics, Computers and Artificial Intelligence (ECAI): IEEE, pp. 1-6.\nChuang, T.-T., and Yadav, S. B. 1998. "The Development of an Adaptive Decision Support System," Decision support systems (24:2), pp. 73-87.\nConfalonieri, M., Barni, A., Valente, A., Cinus, M., and Pedrazzoli, P. 2015. "An Ai Based Decision Support System for Preventive Maintenance and Production Optimization in Energy Intensive Manufacturing Plants," 2015 IEEE International Conference on Engineering, Technology and Innovation/International Technology Management Conference (ICE/ITMC): IEEE, pp. 1-8.\nCunha, A. L., Santos, M. O., Morabito, R., and Barbosa-Póvoa, A. 2018. "An Integrated Approach for Production Lot Sizing and Raw Material Purchasing," European Journal of Operational Research (269:3), pp. 923-938.\nde Oliveira, L. S., Gruetzmacher, S. B., and Teixeira, J. P. 2021. "Covid-19 Time Series Prediction," Procedia Computer Science (181), pp. 973-980.\nDeb, M., Kaur, P., and Sarma, K. K. 2019. "Fuzzy Approach to Decision Support System Design for Inventory Control and Management," Journal of Intelligent Systems (28:4), pp. 549-557.\nDehghani, H., and Bogdanovic, D. 2018. "Copper Price Estimation Using Bat Algorithm," Resources Policy (55), pp. 55-61.\nDumitru, C., and Maria, V. 2013. "Advantages and Disadvantages of Using Neural Networks for Predictions," Ovidius University Annals, Series Economic Sciences (13:1).\nElguindi, J., Hao, X., Lin, Y., Alwathnani, H. A., Wei, G., and Rensing, C. 2011. "Advantages and Challenges of Increased Antimicrobial Copper Use and Copper Mining," Applied microbiology and biotechnology (91:2), pp. 237-249.\nEom, H. B., and Lee, S. M. 1990. "A Survey of Decision Support System Applications (1971–April 1988)," Interfaces (20:3), pp. 65-79.\nFabian, T., Fisher, J., Sasieni, M., and Yardeni, A. 1959. "Purchasing Raw Material on a Fluctuating Market," Operations Research (7:1), pp. 107-122.\nGao, C., Huang, J.-b., Chen, J.-y., Tang, W.-y., Wang, Z.-p., and Liu, J.-x. 2018. "Industrial Transmission Effect of International Metal Price Shocks in Perspective of Industry Chain," Journal of Central South University (25:12), pp. 2929-2943.\nGao, Z., and Tang, L. 2003. "A Multi-Objective Model for Purchasing of Bulk Raw Materials of a Large-Scale Integrated Steel Plant," International Journal of Production Economics (83:3), pp. 325-334.\nGhumman, A. R., Ahmad, S., and Hashmi, H. N. 2018. "Performance Assessment of Artificial Neural Networks and Support Vector Regression Models for Stream Flow Predictions," Environmental monitoring and assessment (190:12), pp. 1-20.\nGinzberg, M. J., and Stohr, E. A. 1982. "Decision Support Systems: Issues and Perspectives,".\nGomez, F., Guzman, J. I., and Tilton, J. E. 2007. "Copper Recycling and Scrap Availability," Resources Policy (32:4), pp. 183-190.\nGorry, G. A., and Scott Morton, M. S. 1971. "A Framework for Management Information Systems,".\nHan, Y., Yang, Y., and Zhou, X. 2013. "Co-Regularized Ensemble for Feature Selection," IJCAI International Joint Conference on Artificial Intelligence.\nHao, J., Li, J., Wu, D., and Sun, X. 2020. "Portfolio Optimisation of Material Purchase Considering Supply Risk–a Multi-Objective Programming Model," International Journal of Production Economics (230), p. 107803.\nKeen, P. G. 1980. "Adaptive Design for Decision Support Systems," Acm Sigoa Newsletter (1:4-5), pp. 15-25.\nKhoshalan, H. A., Shakeri, J., Najmoddini, I., and Asadizadeh, M. 2021. "Forecasting Copper Price by Application of Robust Artificial Intelligence Techniques," Resources Policy (73), p. 102239.\nKingsman, B. G. 1986. "Purchasing Raw Materials with Uncertain Fluctuating Prices," European Journal of Operational Research (25:3), pp. 358-372.\nKolodner, J. L. 1992. "An Introduction to Case-Based Reasoning," Artificial intelligence review (6:1), pp. 3-34.\nKundig, K. J., and Joseph, G. 1998. "Copper: Its Trade Manufacture, Use, and Environmental Status,".\nKwok, T.-Y., and Yeung, D.-Y. 1997. "Constructive Algorithms for Structure Learning in Feedforward Neural Networks for Regression Problems," IEEE transactions on neural networks (8:3), pp. 630-645.\nLasheras, F. S., de Cos Juez, F. J., Sánchez, A. S., Krzemień, A., and Fernández, P. R. 2015. "Forecasting the Comex Copper Spot Price by Means of Neural Networks and Arima Models," Resources Policy (45), pp. 37-43.\nLee, C.-Y., Chou, B.-J., and Huang, C.-F. 2022. "Data Science and Reinforcement Learning for Price Forecasting and Raw Material Procurement in Petrochemical Industry," Advanced Engineering Informatics (51), p. 101443.\nLee, C. K., Lin, D., and Pasari, R. 2014. "Strategic Procurement from Forward Contract and Spot Market," Industrial Management & Data Systems).\nLi, H., and Love, P. E. 1999. "Combining Rule-Based Expert Systems and Artificial Neural Networks for Mark-up Estimation," Construction Management & Economics (17:2), pp. 169-176.\nLi, M., Lian, S., Wang, F., Zhou, Y., Chen, B., Guan, L., and Wu, Y. 2020a. "A Decision Support System Using Hybrid Ai Based on Multi-Image Quality Model and Its Application in Color Design," Future Generation Computer Systems (113), pp. 70-77.\nLi, S.-T., Chiu, K.-C., and Chiu, T.-H. 2020b. "An Application on Building Information Model to Procurement Strategy of Copper Raw Material with Big Data Analytics," 2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM): IEEE, pp. 696-700.\nLiang, J., and Liu, R. 2015. "Stacked Denoising Autoencoder and Dropout Together to Prevent Overfitting in Deep Neural Network," 2015 8th international congress on image and signal processing (CISP): IEEE, pp. 697-701.\nLiu, C., Hu, Z., Li, Y., and Liu, S. 2017. "Forecasting Copper Prices by Decision Tree Learning," Resources Policy (52), pp. 427-434.\nLiu, S., Duffy, A. H., Whitfield, R. I., and Boyle, I. M. 2010. "Integration of Decision Support Systems to Improve Decision Support Performance," Knowledge and Information Systems (22:3), pp. 261-286.\nLiu, S., Zhang, Y., Su, Z., Lu, M., Gu, F., Liu, J., and Jiang, T. 2020a. "Recycling the Domestic Copper Scrap to Address the China’s Copper Sustainability," Journal of Materials Research and Technology (9:3), pp. 2846-2855.\nLiu, Y., Yang, C., Huang, K., and Gui, W. 2020b. "Non-Ferrous Metals Price Forecasting Based on Variational Mode Decomposition and Lstm Network," Knowledge-Based Systems (188), p. 105006.\nMéndez-Suárez, M., García-Fernández, F., and Gallardo, F. 2019. "Artificial Intelligence Modelling Framework for Financial Automated Advising in the Copper Market," Journal of Open Innovation: Technology, Market, and Complexity (5:4), p. 81.\nMa, C., Liu, Z., Cao, Z., Song, W., Zhang, J., and Zeng, W. 2020. "Cost-Sensitive Deep Forest for Price Prediction," Pattern Recognition (107), p. 107499.\nMa, L., and Khorasani, K. 2003. "A New Strategy for Adaptively Constructing Multilayer Feedforward Neural Networks," Neurocomputing (51), pp. 361-385.\nMorales, L., and Andreosso-O’Callaghan, B. 2011. "Comparative Analysis on the Effects of the Asian and Global Financial Crises on Precious Metal Markets," Research in International Business and Finance (25:2), pp. 203-227.\nNavin, G. V. 2015. "Big Data Analytics for Gold Price Forecasting Based on Decision Tree Algorithm and Support Vector Regression (Svr)," International Journal of Science and Research (IJSR) (4:3), pp. 2026-2030.\nO`Keefe, R. M., and Roach, J. W. 1987. "Artificial Intelligence Approaches to Simulation," Journal of the Operational Research Society (38:8), pp. 713-722.\nPower, D. J. 2002. Decision Support Systems: Concepts and Resources for Managers. Greenwood Publishing Group.\nPrentzas, J., and Hatzilygeroudis, I. 2007. "Categorizing Approaches Combining Rule‐Based and Case‐Based Reasoning," Expert Systems (24:2), pp. 97-122.\nRao, N., Brownee, S. M., and Sarma, P. 2004. "Gis-Based Decision Support System for Real Time Water Demand Estimation in Canal Irrigation Systems," Current Science), pp. 628-636.\nRusso, F., and Chilà, G. 2009. "Safety of Users in Road Evacuation: Modelling and Dss for Demand," WIT Transactions on Ecology and the Environment (120), pp. 465-474.\nSachan, S., Yang, J.-B., Xu, D.-L., Benavides, D. E., and Li, Y. 2020. "An Explainable Ai Decision-Support-System to Automate Loan Underwriting," Expert Systems with Applications (144), p. 113100.\nSamuelsson, C., and Björkman, B. 2014. "Copper Recycling," in Handbook of Recycling. Elsevier, pp. 85-94.\nSeguel, F., Carrasco, R., Adasme, P., Alfaro, M., and Soto, I. 2015. "A Meta-Heuristic Approach for Copper Price Forecasting," International Conference on Informatics and Semiotics in Organisations: Springer, pp. 156-165.\nShao, Y., and Wang, S. 2016. "Productivity Growth and Environmental Efficiency of the Nonferrous Metals Industry: An Empirical Study of China," Journal of Cleaner Production (137), pp. 1663-1671.\nSprague Jr, R. H., and Carlson, E. D. 1982. Building Effective Decision Support Systems. Prentice Hall Professional Technical Reference.\nSun, G., Liu, Y., and Lan, Y. 2011. "Fuzzy Two-Stage Material Procurement Planning Problem," Journal of Intelligent Manufacturing (22:2), pp. 319-331.\nTan, C. L., Quah, T. S., and Teh, H. H. 1996. "An Artificial Neural Network That Models Human Decision Making," Computer (29:3), pp. 64-70.\nTsaih, R. 1993. "The Softening Learning Procedure," Mathematical and computer modelling (18:8), pp. 61-64.\nTsaih, R., Hsu, Y., and Lai, C. C. 1998. "Forecasting S&P 500 Stock Index Futures with a Hybrid Ai System," Decision support systems (23:2), pp. 161-174.\nTurban, E., and Watkins, P. R. 1986. "Integrating Expert Systems and Decision Support Systems," Mis Quarterly), pp. 121-136.\nWang, D., Wang, L., Zhang, Z., Wang, D., Zhu, H., Gao, Y., Fan, X., and Tian, F. 2021. "“Brilliant Ai Doctor” in Rural Clinics: Challenges in Ai-Powered Clinical Decision Support System Deployment," Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, pp. 1-18.\nWang, M., Chen, W., Zhou, Y., and Li, X. 2017. "Assessment of Potential Copper Scrap in China and Policy Recommendation," Resources policy (52), pp. 235-244.\nWang, S.-T., and Lin, W.-T. 2010. "Research on Integrating Different Methods of Neural Networks with Case-Based Reasoning and Rule-Based System to Infer Causes of Notebook Computer Breakdown," Expert Systems with Applications (37:6), pp. 4544-4555.\nWu, C., and Chau, K.-W. 2010. "Data-Driven Models for Monthly Streamflow Time Series Prediction," Engineering Applications of Artificial Intelligence (23:8), pp. 1350-1367.\nXiarchos, I. M., and Fletcher, J. J. 2009. "Price and Volatility Transmission between Primary and Scrap Metal Markets," Resources, Conservation and Recycling (53:12), pp. 664-673.\nYalcintas, M., and Akkurt, S. 2005. "Artificial Neural Networks Applications in Building Energy Predictions and a Case Study for Tropical Climates," International journal of energy research (29:10), pp. 891-901.\nYang, R.-H. 2022. An Adaptive Learning-Based Model for Copper Price Forecasting, Master thesis, National Chengchi University, Taipei, Taiwan, pp. 1-78.an Adaptive Learning-Based Model for Copper Price Forecasting."\nYong-quan, L., Shuang-mei, Z., and Kang, Y. 2017. "Concurrent Project Optimal Steel Procurement Strategy in Construction Engineering," Commercial Research (59:2), p. 143.\nZhang, J., Cui, S., Xu, Y., Li, Q., and Li, T. 2018. "A Novel Data-Driven Stock Price Trend Prediction System," Expert Systems with Applications (97), pp. 60-69.; G0109356023; https://nccur.lib.nccu.edu.tw//handle/140.119/141037; https://nccur.lib.nccu.edu.tw/bitstream/140.119/141037/1/602301.pdf

الاتاحة: https://nccur.lib.nccu.edu.tw//handle/140.119/141037
https://doi.org/10.6814/NCCU202200877
https://nccur.lib.nccu.edu.tw/bitstream/140.119/141037/1/602301.pdf

المؤلفون: 李爽

المساهمون: 北京大学城市与环境学院,北京100871

المصدر: 知网 ; 万方 ; http://d.g.wanfangdata.com.cn/Conference_8070989.aspx

مصطلحات موضوعية: 土壤有机碳, GIS分析, 空间回归, 趋势预测

Relation: 中国地理学会2009百年庆典学术大会.北京,2009/10/17.; 860003; http://hdl.handle.net/20.500.11897/70788

الاتاحة: https://hdl.handle.net/20.500.11897/70788

المؤلفون: 孟蕾

المساهمون: 北京大学人民医院心脏外科

المصدر: 知网

مصطلحات موضوعية: 冠脉旁路移植术, 老年人口, 人口总数, 中国人口老龄化, 监护时间, 冠状动脉搭桥术, 发展趋势预测, 心排出量, 双腔心脏起搏器, 低氧血症

Relation: 全国内科护理学术交流暨专题讲座会议、全国心脏内、外科护理学术交流暨专题讲座会议.; 822656; http://hdl.handle.net/20.500.11897/127526

الاتاحة: https://hdl.handle.net/20.500.11897/127526

المؤلفون: 劉昭麟

المساهمون: 中華民國人工智慧學會, 國立政治大學資訊科學系

مصطلحات موضوعية: 股價漲跌趨勢預測, 文字探勘技術, 文字分類技術

Relation: 第十一屆人工智慧與應用研討會論文集; https://nccur.lib.nccu.edu.tw//handle/140.119/39660

الاتاحة: https://nccur.lib.nccu.edu.tw//handle/140.119/39660

المؤلفون: 刘洋, 吴远浩, 郑玉峰, 奚廷斐

المساهمون: 北京大学工学院材料科学与工程系 北京 100871, 北京大学前沿交叉学科研究院生物医用材料与组织工程中心 北京 100871

المصدر: 万方 ; 知网 ; http://d.g.wanfangdata.com.cn/Periodical_zgylqxxx201409002.aspx

مصطلحات موضوعية: 介入装置及器械 微创 发展趋势 预测 interventional devices minimal invasiveness tendency prediction

Relation: 中国医疗器械信息.2014,(9),1-8.; 824619; http://hdl.handle.net/20.500.11897/223407

الاتاحة: https://hdl.handle.net/20.500.11897/223407
https://doi.org/10.3969/j.issn.1006-6586.2014.09.002

المؤلفون: 殷蜀梅, 李春英

المساهمون: 100191,北京大学医学图书馆

المصدر: 万方 ; http://d.g.wanfangdata.com.cn/Periodical_zhyxkyglzz201402014.aspx

مصطلحات موضوعية: 文本挖掘, 胰岛淀粉样多肽, 趋势预测, Text mining, Islet amyloid polypeptide, Emerging trend detecting

Relation: 中华医学科研管理杂志.2014,27,(2),162-166.; 1123130; http://hdl.handle.net/20.500.11897/168998

الاتاحة: https://hdl.handle.net/20.500.11897/168998
https://doi.org/10.3760/cma.j.issn.1006-1924.2014.02.014

المؤلفون: 张志雄, 奚廷斐

المساهمون: 北京大学深圳研究院生物医学工程中心 深圳 518057, 北京大学前沿交叉学科研究院生物医用材料与组织工程中心 北京 100871

المصدر: 万方 ; http://d.g.wanfangdata.com.cn/Periodical_zgylqxxx201308002.aspx

مصطلحات موضوعية: 眼科 生物医用材料 发展趋势 预测 ophthalmology biomedical materials tendency prediction

Relation: 中国医疗器械信息.2013,(8),6-9,59.; 1129904; http://hdl.handle.net/20.500.11897/266563

الاتاحة: https://hdl.handle.net/20.500.11897/266563
https://doi.org/10.3969/j.issn.1006-6586.2013.08.002

المؤلفون: 寸雪涛

المساهمون: 广西民族大学外国语学院

مصطلحات موضوعية: 德菲尔法, 东盟国家语种, 专业发展, 趋势预测

Relation: 高教论坛,2012(01):61-63; http://ir.calis.edu.cn/hdl/530500/20272

الاتاحة: http://ir.calis.edu.cn/hdl/530500/20272