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Modified support vector machines in financial time series forecasting.

, and . Neurocomputing, 48 (1-4): 847-861 (2002)

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Neuro-Genetic Based Method to the Classification of Acupuncture Needle: A Case Study., and . GECCO, page 99-105. Morgan Kaufmann, (1999)Scalable privacy-preserving participant selection in mobile crowd sensing., , , , , , and . PerCom, page 59-68. IEEE Computer Society, (2017)Adaptive Multiple Metrics Routing Protocols for Heterogeneous Multi-Hop Wireless Networks., , , and . CCNC, page 13-17. IEEE, (2008)An Unsupervised Feature Extraction Method based on Multi-granularity Convolution Denoising Autoencoder., , and . ICIS, page 118-123. IEEE, (2019)c-ascending support vector machines for financial time series forecasting., , and . CIFEr, page 317-323. IEEE, (2003)Feature Selection for Support Vector Machines., and . IDEAL, volume 1983 of Lecture Notes in Computer Science, page 268-273. Springer, (2000)epsilon-Descending Support Vector Machines for Financial Time Series Forecasting., and . IDEAL, volume 1983 of Lecture Notes in Computer Science, page 274-279. Springer, (2000)A Hybrid Anycast Routing Protocol for Load Balancing in Heterogeneous Access Networks., , , and . ICCCN, page 99-104. IEEE, (2008)An Active and Collaborative Approach to Teaching Discrete Structures., and . SIGCSE, page 822-827. ACM, (2018)Research on Enterprises Loss in Regional Economic Risk Management., , , , , , , , , and . TrustCom, page 1485-1490. IEEE, (2022)