On neural networks and learning systems for business computing
暂无分享,去创建一个
Liu Yang | Yawen Li | Weifeng Jiang | Tian Wu | Tian Wu | Yawen Li | Liu Yang | Weifeng Jiang
[1] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[2] Desheng Dash Wu,et al. Business intelligence in risk management: Some recent progresses , 2014, Inf. Sci..
[3] M.L. Nasir,et al. Predicting corporate bankruptcy using modular neural networks , 2000, Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520).
[4] Tai-Yue Wang,et al. Forecasting innovation performance via neural networks—a case of Taiwanese manufacturing industry , 2006 .
[5] Vesna Bosilj-Vuksic,et al. Supporting Performance Management with Business Process Management and Business Intelligence: A Case Analysis of Integration and Orchestration , 2013, Int. J. Inf. Manag..
[6] Michal Tkác,et al. Artificial neural networks in business: Two decades of research , 2016, Appl. Soft Comput..
[7] Raymond Y. K. Lau,et al. Demystifying Big Data Analytics for Business Intelligence Through the Lens of Marketing Mix , 2015, Big Data Res..
[8] Li-Min Chuang,et al. Evolution of National Entrepreneurial Opportunity Recognition: A Neural Network Analysis , 2013 .
[9] R. Rajnoha,et al. Business intelligence as a key information and knowledge tool for strategic business performance management , 2016 .
[10] Donald Michie,et al. Machine Learning in the Next Five Years , 1988, EWSL.
[11] Yi-Chung Hu,et al. Applying Backpropagation Neural Networks to Bankruptcy Prediction , 2005, Int. J. Electron. Bus. Manag..
[12] Xiaoyong Du,et al. Big data challenge: a data management perspective , 2013, Frontiers of Computer Science.
[13] RadhaKanta Mahapatra,et al. Business data mining - a machine learning perspective , 2001, Inf. Manag..
[14] A.VictorDevadoss,et al. ADOPTION OF NEURAL NETWORK IN FORECASTING THE TRENDS OF STOCK MARKET , 2013 .
[15] Robert Winter,et al. Aligning Process Automation and Business Intelligence to Support Corporate Performance Management , 2004, AMCIS.
[16] A. Gunasekaran,et al. Big data analytics in logistics and supply chain management: Certain investigations for research and applications , 2016 .
[17] Min-Yuh Day,et al. Deep learning for financial sentiment analysis on finance news providers , 2016, 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).
[18] Raul Valverde,et al. A Business Intelligence System for Risk Management in the Real Estate Industry , 2011 .
[19] Xin Jin,et al. Knowledge source strategy and enterprise innovation performance: dynamic analysis based on machine learning , 2018, Technol. Anal. Strateg. Manag..
[20] Marius Cioca,et al. Machine Learning and Creative Methods Used to Classify Customers in a CRM Systems , 2013 .
[21] Jan Hendrik Witte,et al. Deep Learning for Finance: Deep Portfolios , 2016 .
[22] Yong Geng,et al. Co-benefit evaluation for urban public transportation sector – a case of Shenyang, China , 2013 .
[23] Maysam Abbod,et al. A novel hybrid ensemble model to predict FTSE100 index by combining neural network and EEMD , 2015, 2015 European Control Conference (ECC).
[24] Qiang Yang,et al. A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.
[25] Ross P. Buckley,et al. The Evolution of Fintech: A New Post-Crisis Paradigm? , 2015 .
[26] Bongsik Shin,et al. Data quality management, data usage experience and acquisition intention of big data analytics , 2014, Int. J. Inf. Manag..
[27] Jianguo Du,et al. Application of Machine Learning Methods to Risk Assessment of Financial Statement Fraud: Evidence from China , 2014 .
[28] Gérard Bloch,et al. Incorporating prior knowledge in support vector machines for classification: A review , 2008, Neurocomputing.
[29] Veda C. Storey,et al. Business Intelligence and Analytics: From Big Data to Big Impact , 2012, MIS Q..
[30] Michel Happiette,et al. A neural clustering and classification system for sales forecasting of new apparel items , 2007, Appl. Soft Comput..
[31] A. Jaffe. Real Effects of Academic Research , 1989 .
[32] M. Spott,et al. Operational risk management with real-time business intelligence , 2007 .
[33] Koen Bertels,et al. Qualitative company performance evaluation: Linear discriminant analysis and neural network models , 1999, Eur. J. Oper. Res..
[34] Tahir Alyas,et al. Forecasting of Intellectual Capital by Measuring Innovation Using Adaptive Neuro-Fuzzy Inference System , 2015 .
[35] Seniye Ümit Oktay Fırat,et al. Sustainability, Risk, and Business Intelligence in Supply Chains , 2016 .
[36] Arash Bahrammirzaee,et al. A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems , 2010, Neural Computing and Applications.
[37] Shahriar Akter,et al. How ‘Big Data’ Can Make Big Impact: Findings from a Systematic Review and a Longitudinal Case Study , 2015 .
[38] Liu Zhi,et al. Energy efficiency evaluation method based on deep learning model , 2016, 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC).
[39] Angappa Gunasekaran,et al. The impact of big data on world-class sustainable manufacturing , 2015, The International Journal of Advanced Manufacturing Technology.
[40] Ammar Belatreche,et al. Evaluating machine learning classification for financial trading: An empirical approach , 2016, Expert Syst. Appl..
[41] W. Scott Spangler,et al. The integration of business intelligence and knowledge management , 2002, IBM Syst. J..
[42] Kimon P. Valavanis,et al. Forecasting stock market short-term trends using a neuro-fuzzy based methodology , 2009, Expert Syst. Appl..
[43] Tong Zhu,et al. Transport solutions for cleaner air , 2016, Science.
[44] David West,et al. Neural network ensemble strategies for financial decision applications , 2005, Comput. Oper. Res..
[45] Dorian Pyle,et al. Data Preparation for Data Mining , 1999 .
[46] John T. Stasko,et al. Understanding Interfirm Relationships in Business Ecosystems with Interactive Visualization , 2013, IEEE Transactions on Visualization and Computer Graphics.
[47] Razieh Tabandeh,et al. The Application of Artificial Neural Network Method to Investigate the Effect of Unemployment on Tax Evasion , 2015 .
[48] Li De,et al. Artificial Intelligence with Uncertainty , 2004 .
[49] Kwai-Sang Chin,et al. A neural network-based approach of quantifying relative importance among various determinants toward organizational innovation , 2011, Expert Syst. Appl..
[50] Yongtae Park,et al. The impact of R&D collaboration on innovative performance in Korea: A Bayesian network approach , 2008, Scientometrics.
[51] Hans-Dieter Zimmermann,et al. Social commerce research: An integrated view , 2013, Electron. Commer. Res. Appl..
[52] Yan Shi,et al. The Role of Business Intelligence in Business Performance Management , 2010, 2010 3rd International Conference on Information Management, Innovation Management and Industrial Engineering.
[53] Wei-Yang Lin,et al. Machine Learning in Financial Crisis Prediction: A Survey , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[54] Marion O. Adebiyi,et al. Stock Price Prediction using Neural Network with Hybridized Market Indicators , 2012 .
[55] Pugna Irina Bogdana,et al. The Role Of Business Intelligence In Business Performance Management , 2009 .
[56] Soushan Wu,et al. Comparison of support-vector machines and back propagation neural networks in forecasting the six major Asian stock markets , 2006 .
[57] Hassouna Fedhila,et al. The effect of internal R&D efforts and external technology sourcing on achieving innovations in developing countries: the case of Tunisian manufacturing firms , 2010 .
[58] Thankom Gopinath Arun,et al. Handbook of Research on Green Economic Development Initiatives and Strategies , 2016 .
[59] Haixia Zhang. Research and Modelling on the E-commerce Consumer Behavior based on Intelligent Recommendation System and Machine Learning , 2016 .
[60] Peng-Yeng Yin,et al. Risk management of wind farm micro-siting using an enhanced genetic algorithm with simulation optimization , 2017 .
[61] M. Quaddus,et al. A multiple objective optimization based QFD approach for efficient resilient strategies to mitigate supply chain vulnerabilities: The case of garment industry of Bangladesh , 2015 .
[62] Marcin Relich. Knowledge acquisition for new product development with the use of an ERP database , 2013, 2013 Federated Conference on Computer Science and Information Systems.
[63] Mark I. Hwang,et al. A fuzzy neural network for assessing the risk of fraudulent financial reporting , 2003 .
[64] Jason Weston,et al. Deep learning via semi-supervised embedding , 2008, ICML '08.
[65] T. Schoenherr,et al. Data Science, Predictive Analytics, and Big Data in Supply Chain Management: Current State and Future Potential , 2015 .
[66] Spyros Makridakis,et al. The Forthcoming Artificial Intelligence (AI) Revolution: Its Impact on Society and Firms , 2017 .
[67] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[68] Xin Li,et al. Application of Neural Networks in Financial Data Mining , 2007, International Conference on Computational Intelligence.
[69] Rajeev Sharma,et al. Transforming Decision-Making Processes Transforming decision-making processes : a research agenda for understanding the impact of business analytics on organizations , 2017 .
[70] Marijana Zekic-Susac,et al. Modelling small-business credit scoring by using logistic regression, neural networks and decision trees , 2005, Intell. Syst. Account. Finance Manag..
[71] Yi-Chung Hu,et al. Comparing four bankruptcy prediction models: Logit, quadratic interval logit, neural and fuzzy neural networks , 2010, Expert Syst. Appl..
[72] Kuan Yew Wong,et al. A Neural Network Approach for Predicting Manufacturing Performance using Knowledge Management Metrics , 2017, Cybern. Syst..
[73] Richard F. Hartl,et al. Supply chain dynamics, control and disruption management , 2016 .
[74] Carol E. Brown,et al. Artificial neural networks in accounting and finance: modeling issues , 2000, Intell. Syst. Account. Finance Manag..
[75] S. Fawcett,et al. Data Science, Predictive Analytics, and Big Data: A Revolution that Will Transform Supply Chain Design and Management , 2013 .
[76] M. Christopher,et al. The Supply Chain Becomes the Demand Chain , 2014 .
[77] Benjamin T. Hazen,et al. Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications , 2014 .
[78] Hing Kai Chan,et al. Recent Development in Big Data Analytics for Business Operations and Risk Management , 2017, IEEE Transactions on Cybernetics.
[79] Ching-Tzu Tsai,et al. Comparing ANFIS and SEM in linear and nonlinear forecasting of new product development performance , 2011, Expert Syst. Appl..
[80] Marc J. Schniederjans,et al. A comparison between Fama and French's model and artificial neural networks in predicting the Chinese stock market , 2005, Comput. Oper. Res..
[81] Dilek Penpece,et al. Predicting Sales Revenue by Using Artificial Neural Network in Grocery Retailing Industry: A Case Study in Turkey , 2014 .
[82] A. Hossain,et al. Comparison of GARCH and neural network methods in financial time series prediction , 2008, 2008 11th International Conference on Computer and Information Technology.
[83] Woosik Lee,et al. A deep learning analysis of the KOSPI’s directions , 2017 .
[84] Klaus-Dieter Thoben,et al. An approach to monitoring quality in manufacturing using supervised machine learning on product state data , 2013, Journal of Intelligent Manufacturing.
[85] Armando Vieira,et al. Business Applications of Deep Learning , 2020, Natural Language Processing.
[86] Mehdi Khashei,et al. A new hybrid artificial neural networks and fuzzy regression model for time series forecasting , 2008, Fuzzy Sets Syst..
[87] Mohammad Sadeghzadeh Maharluie,et al. Detecting and ranking cash flow risk factors via artificial neural networks technique , 2016 .
[88] Zhaohui Wu,et al. Toward Risk Reduction for Mobile Service Composition , 2016, IEEE Transactions on Cybernetics.
[89] Carol E. Brown,et al. Artificial neural networks in accounting and finance: modeling issues , 2000 .
[90] J. Mentzer,et al. The Effects of Entrepreneurial Proclivity and Market Orientation on Business Performance , 2002 .
[91] Lu Zhao,et al. Optimizing enterprise risk management: a literature review and critical analysis of the work of Wu and Olson , 2016, Ann. Oper. Res..
[92] Jayanthi Ranjan,et al. Real time business intelligence in supply chain analytics , 2008, Inf. Manag. Comput. Secur..
[93] Nicholas G. Polson,et al. Deep Learning in Finance , 2016, ArXiv.
[94] Jing Zhao,et al. ACOSampling: An ant colony optimization-based undersampling method for classifying imbalanced DNA microarray data , 2013, Neurocomputing.
[95] Kerim Goztepe,et al. A Study on Innovation Performance Forecasting in Advanced Military Education Using Neuro-Fuzzy Networks , 2013 .
[96] Nicholas G. Polson,et al. Deep learning for finance: deep portfolios: J. B. HEATON, N. G. POLSON AND J. H. WITTE , 2017 .
[97] Deyi Li,et al. Artificial Intelligence with Uncertainty , 2004, CIT.
[98] Marcin Relich. A Decision Support System for Alternative Project Choice Based on Fuzzy Neutral Networks , 2010 .
[99] Junyu Dong,et al. An Overview on Data Representation Learning: From Traditional Feature Learning to Recent Deep Learning , 2016, ArXiv.
[100] Seetha Hari,et al. Learning From Imbalanced Data , 2019, Advances in Computer and Electrical Engineering.
[101] Petr Hájek,et al. Mining corporate annual reports for intelligent detection of financial statement fraud - A comparative study of machine learning methods , 2017, Knowl. Based Syst..
[102] M. Relich,et al. Assessment of task duration in investment projects , 2010 .
[103] Hui Xiong,et al. Collaborative Company Profiling: Insights from an Employee's Perspective , 2017, AAAI.
[104] Paulo Cortez,et al. Business intelligence in banking: A literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation , 2015, Expert Syst. Appl..
[105] Constantin Zopounidis,et al. CREDIT CARD APPLICATION ASSESSMENT USING A NEURO-FUZZY CLASSIFICATION SYSTEM , 2006 .
[106] Tsan-Ming Choi,et al. Optimal Bi-Objective Redundancy Allocation for Systems Reliability and Risk Management , 2016, IEEE Transactions on Cybernetics.
[107] Xu Ji,et al. The knowledge modeling system of ready-mixed concrete enterprise and artificial intelligence with ANN-GA for manufacturing production , 2016, J. Intell. Manuf..
[108] Thomas Fischer,et al. Deep learning with long short-term memory networks for financial market predictions , 2017, Eur. J. Oper. Res..
[109] Klaus-Dieter Thoben,et al. Machine learning in manufacturing: advantages, challenges, and applications , 2016 .
[110] F. Creutzig,et al. Energy and environment. Transport: A roadblock to climate change mitigation? , 2015, Science.
[111] Yudong Zhang,et al. Stock market prediction of S&P 500 via combination of improved BCO approach and BP neural network , 2009, Expert Syst. Appl..
[112] Nagraj Balakrishnan,et al. Modeling the relationship between corporate strategy and wealth creation using neural networks , 2000, Comput. Oper. Res..
[113] Ali Uyar,et al. The impact of multinationality on firm value: A comparative analysis of machine learning techniques , 2014, Decis. Support Syst..
[114] Taghi M. Khoshgoftaar,et al. Deep learning applications and challenges in big data analytics , 2015, Journal of Big Data.
[115] A. Lo,et al. Consumer Credit Risk Models Via Machine-Learning Algorithms , 2010 .
[116] Ying-Chyi Chou,et al. Developing a temporary workforce transaction mechanism from risk sharing perspectives , 2018, Int. J. Prod. Res..
[117] Guanghui Zhou,et al. Development of electric vehicles use in China: A study from the perspective of life-cycle energy consumption and greenhouse gas emissions , 2013 .
[118] Davide Aloini,et al. Risk management in ERP project introduction: Review of the literature , 2007, Inf. Manag..
[119] Jae Kwon Bae,et al. Using machine learning algorithms for housing price prediction: The case of Fairfax County, Virginia housing data , 2015, Expert Syst. Appl..
[120] N. Chater,et al. Ten years of the rational analysis of cognition , 1999, Trends in Cognitive Sciences.
[121] KhasheiMehdi,et al. A new hybrid artificial neural networks and fuzzy regression model for time series forecasting , 2008 .
[122] Maria Schuld,et al. Implementing a distance-based classifier with a quantum interference circuit , 2017, 1703.10793.
[123] Marcin Relich. A DECISION SUPPORT SYSTEM FOR ALTERNATIVE PROJECT CHOICE BASED ON FUZZY NEURAL NETWORKS , 2010 .
[124] Murtaza Haider,et al. Beyond the hype: Big data concepts, methods, and analytics , 2015, Int. J. Inf. Manag..
[125] Yu-Shan Chen,et al. Analyzing the nonlinear effects of firm size, profitability, and employee productivity on patent citations of the US pharmaceutical companies by using artificial neural network , 2009, Scientometrics.