The Influencing Factors, Regional Difference and Temporal Variation of Industrial Technology Innovation: Evidence with the FOA-GRNN Model
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- Xiangdong Chen & Ruixi Li & Xin Niu & Ulrich Hilpert & Valerie Hunstock, 2018. "Metropolitan Innovation and Sustainability in China—A Double Lens Perspective on Regional Development," Sustainability, MDPI, vol. 10(2), pages 1-26, February.
- Yue-Gang Song & Yu-Long Zhou & Ren-Jie Han, 2018. "Neural networks for stock price prediction," Papers 1805.11317, arXiv.org.
- Chengliang Liu & Qingbin Guo, 2019. "Technology Spillover Effect in China: The Spatiotemporal Evolution and Its Drivers," Sustainability, MDPI, vol. 11(6), pages 1-14, March.
- Jugend, Daniel & Fiorini, Paula De Camargo & Armellini, Fabiano & Ferrari, Aline Gabriela, 2020. "Public support for innovation: A systematic review of the literature and implications for open innovation," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
- Tsui-Yii Shih, 2018. "Determinants of Enterprises Radical Innovation and Performance: Insights into Strategic Orientation of Cultural and Creative Enterprises," Sustainability, MDPI, vol. 10(6), pages 1-22, June.
- Jiangfeng Hu & Zhao Wang & Qinghua Huang & Xiaoqin Zhang, 2019. "Environmental Regulation Intensity, Foreign Direct Investment, and Green Technology Spillover—An Empirical Study," Sustainability, MDPI, vol. 11(10), pages 1-15, May.
- Liang, Yi & Niu, Dongxiao & Hong, Wei-Chiang, 2019. "Short term load forecasting based on feature extraction and improved general regression neural network model," Energy, Elsevier, vol. 166(C), pages 653-663.
- Bahoo, Salman & Cucculelli, Marco & Qamar, Dawood, 2023. "Artificial intelligence and corporate innovation: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
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Keywords
technology innovation; influencing factors; GRNN; FOA;All these keywords.
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