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人工神经网络 (查看源代码)

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由于他们重现和模拟非线性过程的能力，人工神经网络在广泛的领域建立了很多应用。

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~~应用领域包括【系统识别】和控制（车辆控制，弹道预测，~~<ref>{{cite journal|last1=Zissis|first1=Dimitrios|title=A cloud based architecture capable of perceiving and predicting multiple vessel behaviour|journal=Applied Soft Computing|date=October 2015|volume=35|url=http://www.sciencedirect.com/science/article/pii/S1568494615004329|doi=10.1016/j.asoc.2015.07.002|pages=652–661}}</ref>~~【过程控制】，【自然资源管理】），量子化学，~~<ref name="Balabin_2009">{{Cite journal|journal=[[J. Chem. Phys.]] |volume = 131 |issue = 7 |page = 074104 |doi=10.1063/1.3206326 |title=Neural network approach to quantum-chemistry data: Accurate prediction of density functional theory energies |year=2009 |author1=Roman M. Balabin |author2=Ekaterina I. Lomakina |pmid=19708729|bibcode = 2009JChPh.131g4104B }}</ref>~~玩游戏和【决策】（西洋双陆棋，国际象棋，扑克），【模式识别】（雷达系统，【人脸识别】，信号分类，~~<ref>{{cite journal|last=Sengupta|first=Nandini|author2=Sahidullah, Md|author3=Saha, Goutam|title=Lung sound classification using cepstral-based statistical features|journal=Computers in Biology and Medicine|date=August 2016|volume=75|issue=1|pages=118–129|doi=10.1016/j.compbiomed.2016.05.013|url=http://www.sciencedirect.com/science/article/pii/S0010482516301263}}</ref>~~物体识别和其他），序列识别（姿态，语音，手写和印刷文本），【医疗诊断】，金融~~<ref>{{cite journal|last1=French|first1=Jordan|title=The time traveller's CAPM|journal=Investment Analysts Journal|volume=46|issue=2|pages=81–96|doi=10.1080/10293523.2016.1255469|url=http://www.tandfonline.com/doi/abs/10.1080/10293523.2016.1255469|year=2016}}</ref>~~（例如【自动交易系统】），【数据挖掘】，可视化，【机器翻译】，社交网络滤波和【垃圾邮件】滤波。~~<ref>{{Cite news|url=https://www.wsj.com/articles/facebook-boosts-a-i-to-block-terrorist-propaganda-1497546000|title=Facebook Boosts A.I. to Block Terrorist Propaganda|last=Schechner|first=Sam|date=2017-06-15|work=Wall Street Journal|access-date=2017-06-16|language=en-US|issn=0099-9660}}</ref>

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应用领域包括[https://en.wikipedia.org/wiki/System_identification 系统识别]和控制（车辆控制，弹道预测，<ref>{{cite journal|last1=Zissis|first1=Dimitrios|title=A cloud based architecture capable of perceiving and predicting multiple vessel behaviour|journal=Applied Soft Computing|date=October 2015|volume=35|url=http://www.sciencedirect.com/science/article/pii/S1568494615004329|doi=10.1016/j.asoc.2015.07.002|pages=652–661}}</ref>[https://en.wikipedia.org/wiki/Process_control 过程控制]，[https://en.wikipedia.org/wiki/Natural_resource_management 自然资源管理]），量子化学，<ref name="Balabin_2009">{{Cite journal|journal=[[J. Chem. Phys.]] |volume = 131 |issue = 7 |page = 074104 |doi=10.1063/1.3206326 |title=Neural network approach to quantum-chemistry data: Accurate prediction of density functional theory energies |year=2009 |author1=Roman M. Balabin |author2=Ekaterina I. Lomakina |pmid=19708729|bibcode = 2009JChPh.131g4104B }}</ref>玩游戏和[https://en.wikipedia.org/wiki/Decision_making 决策]（西洋双陆棋，国际象棋，扑克），[https://en.wikipedia.org/wiki/Pattern_recognition 模式识别]（雷达系统，[https://en.wikipedia.org/wiki/Facial_recognition_system 人脸识别]，信号分类，<ref>{{cite journal|last=Sengupta|first=Nandini|author2=Sahidullah, Md|author3=Saha, Goutam|title=Lung sound classification using cepstral-based statistical features|journal=Computers in Biology and Medicine|date=August 2016|volume=75|issue=1|pages=118–129|doi=10.1016/j.compbiomed.2016.05.013|url=http://www.sciencedirect.com/science/article/pii/S0010482516301263}}</ref>物体识别和其他），序列识别（姿态，语音，手写和印刷文本），[https://en.wikipedia.org/wiki/Medical_diagnosis 医疗诊断]，金融<ref>{{cite journal|last1=French|first1=Jordan|title=The time traveller's CAPM|journal=Investment Analysts Journal|volume=46|issue=2|pages=81–96|doi=10.1080/10293523.2016.1255469|url=http://www.tandfonline.com/doi/abs/10.1080/10293523.2016.1255469|year=2016}}</ref>（例如[https://en.wikipedia.org/wiki/Algorithmic_trading 自动交易系统]），[https://en.wikipedia.org/wiki/Data_mining 数据挖掘]，可视化，[https://en.wikipedia.org/wiki/Machine_translation 机器翻译]，社交网络滤波和[https://en.wikipedia.org/wiki/E-mail_spam 垃圾邮件]滤波。<ref>{{Cite news|url=https://www.wsj.com/articles/facebook-boosts-a-i-to-block-terrorist-propaganda-1497546000|title=Facebook Boosts A.I. to Block Terrorist Propaganda|last=Schechner|first=Sam|date=2017-06-15|work=Wall Street Journal|access-date=2017-06-16|language=en-US|issn=0099-9660}}</ref>

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~~ANN被用于诊断癌症，包括【肺癌】，~~<ref>{{cite web|last=Ganesan|first=N|title=Application of Neural Networks in Diagnosing Cancer Disease Using Demographic Data|url=http://www.ijcaonline.org/journal/number26/pxc387783.pdf|publisher=International Journal of Computer Applications}}</ref>~~【前列腺癌】，【结肠直肠癌】~~<ref>{{cite web|url=http://www.lcc.uma.es/~jja/recidiva/042.pdf|title=Artificial Neural Networks Applied to Outcome Prediction for Colorectal Cancer Patients in Separate Institutions|last=Bottaci|first=Leonardo|publisher=The Lancet}}</ref> 和只使用细胞形状信息区分高度浸润性癌细胞系和较少浸润性系。<ref>{{cite journal|last2=Lyons|first2=Samanthe M|last3=Castle|first3=Jordan M|last4=Prasad|first4=Ashok|date=2016|title=Measuring systematic changes in invasive cancer cell shape using Zernike moments|url=http://pubs.rsc.org/en/Content/ArticleLanding/2016/IB/C6IB00100A#!divAbstract|journal=Integrative Biology|volume=8|issue=11|pages=1183–1193|doi=10.1039/C6IB00100A|pmid=27735002|last1=Alizadeh|first1=Elaheh}}</ref><ref>{{cite journal|date=2016|title=Changes in cell shape are correlated with metastatic potential in murine|url=http://bio.biologists.org/content/5/3/289|journal=Biology Open|volume=5|issue=3|pages=289–299|doi=10.1242/bio.013409|last1=Lyons|first1=Samanthe}}</ref>

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ANN被用于诊断癌症，包括[https://en.wikipedia.org/wiki/Lung_cancer 肺癌]，<ref>{{cite web|last=Ganesan|first=N|title=Application of Neural Networks in Diagnosing Cancer Disease Using Demographic Data|url=http://www.ijcaonline.org/journal/number26/pxc387783.pdf|publisher=International Journal of Computer Applications}}</ref>[https://en.wikipedia.org/wiki/Prostate_cancer 前列腺癌]，[https://en.wikipedia.org/wiki/Colorectal_cancer 结肠直肠癌]<ref>{{cite web|url=http://www.lcc.uma.es/~jja/recidiva/042.pdf|title=Artificial Neural Networks Applied to Outcome Prediction for Colorectal Cancer Patients in Separate Institutions|last=Bottaci|first=Leonardo|publisher=The Lancet}}</ref> 和只使用细胞形状信息区分高度浸润性癌细胞系和较少浸润性系。<ref>{{cite journal|last2=Lyons|first2=Samanthe M|last3=Castle|first3=Jordan M|last4=Prasad|first4=Ashok|date=2016|title=Measuring systematic changes in invasive cancer cell shape using Zernike moments|url=http://pubs.rsc.org/en/Content/ArticleLanding/2016/IB/C6IB00100A#!divAbstract|journal=Integrative Biology|volume=8|issue=11|pages=1183–1193|doi=10.1039/C6IB00100A|pmid=27735002|last1=Alizadeh|first1=Elaheh}}</ref><ref>{{cite journal|date=2016|title=Changes in cell shape are correlated with metastatic potential in murine|url=http://bio.biologists.org/content/5/3/289|journal=Biology Open|volume=5|issue=3|pages=289–299|doi=10.1242/bio.013409|last1=Lyons|first1=Samanthe}}</ref>

ANN被用于加速基础设施遭受自然灾害的可靠性分析。<ref>{{cite arxiv|last=Nabian|first=Mohammad Amin|last2=Meidani|first2=Hadi|date=2017-08-28|title=Deep Learning for Accelerated Reliability Analysis of Infrastructure Networks|eprint=1708.08551|class=cs.CE}}</ref><ref>{{Cite journal|last=Nabian|first=Mohammad Amin|last2=Meidani|first2=Hadi|date=2018|title=Accelerating Stochastic Assessment of Post-Earthquake Transportation Network Connectivity via Machine-Learning-Based Surrogates|url=https://trid.trb.org/view/1496617|journal=Transportation Research Board 97th Annual Meeting|volume=|pages=|via=}}</ref>

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~~ANN也被用于在【地球科学】中建立黑箱模型，【水文学】，~~<ref>{{Cite journal|last=null null|date=2000-04-01|title=Artificial Neural Networks in Hydrology. I: Preliminary Concepts|url=http://ascelibrary.org/doi/abs/10.1061/(ASCE)1084-0699(2000)5:2(115)|journal=Journal of Hydrologic Engineering|volume=5|issue=2|pages=115–123|doi=10.1061/(ASCE)1084-0699(2000)5:2(115)}}</ref><ref>{{Cite journal|last=null null|date=2000-04-01|title=Artificial Neural Networks in Hydrology. II: Hydrologic Applications|url=http://ascelibrary.org/doi/abs/10.1061/(ASCE)1084-0699(2000)5:2(124)|journal=Journal of Hydrologic Engineering|volume=5|issue=2|pages=124–137|doi=10.1061/(ASCE)1084-0699(2000)5:2(124)}}</ref>~~海洋建模，【海岸工程】~~<ref>{{Cite journal|last=Peres|first=D. J.|last2=Iuppa|first2=C.|last3=Cavallaro|first3=L.|last4=Cancelliere|first4=A.|last5=Foti|first5=E.|date=2015-10-01|title=Significant wave height record extension by neural networks and reanalysis wind data|url=http://www.sciencedirect.com/science/article/pii/S1463500315001432|journal=Ocean Modelling|volume=94|pages=128–140|doi=10.1016/j.ocemod.2015.08.002|bibcode=2015OcMod..94..128P}}</ref><ref>{{Cite journal|last=Dwarakish|first=G. S.|last2=Rakshith|first2=Shetty|last3=Natesan|first3=Usha|date=2013|title=Review on Applications of Neural Network in Coastal Engineering|url=http://www.ciitresearch.org/dl/index.php/aiml/article/view/AIML072013007|journal=Artificial Intelligent Systems and Machine Learning|language=English|volume=5|issue=7|pages=324–331}}</ref> ~~和【地貌学】~~<ref>{{Cite journal|last=Ermini|first=Leonardo|last2=Catani|first2=Filippo|last3=Casagli|first3=Nicola|date=2005-03-01|title=Artificial Neural Networks applied to landslide susceptibility assessment|url=http://www.sciencedirect.com/science/article/pii/S0169555X04002272|journal=Geomorphology|series=Geomorphological hazard and human impact in mountain environments|volume=66|issue=1|pages=327–343|doi=10.1016/j.geomorph.2004.09.025|bibcode=2005Geomo..66..327E}}</ref>只是其中很少的几个例子。

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ANN也被用于在[https://en.wikipedia.org/wiki/Geoscience 地球科学]中建立黑箱模型，[https://en.wikipedia.org/wiki/Hydrology 水文学]，<ref>{{Cite journal|last=null null|date=2000-04-01|title=Artificial Neural Networks in Hydrology. I: Preliminary Concepts|url=http://ascelibrary.org/doi/abs/10.1061/(ASCE)1084-0699(2000)5:2(115)|journal=Journal of Hydrologic Engineering|volume=5|issue=2|pages=115–123|doi=10.1061/(ASCE)1084-0699(2000)5:2(115)}}</ref><ref>{{Cite journal|last=null null|date=2000-04-01|title=Artificial Neural Networks in Hydrology. II: Hydrologic Applications|url=http://ascelibrary.org/doi/abs/10.1061/(ASCE)1084-0699(2000)5:2(124)|journal=Journal of Hydrologic Engineering|volume=5|issue=2|pages=124–137|doi=10.1061/(ASCE)1084-0699(2000)5:2(124)}}</ref>海洋建模，[https://en.wikipedia.org/wiki/Coastal_engineering 海岸工程]<ref>{{Cite journal|last=Peres|first=D. J.|last2=Iuppa|first2=C.|last3=Cavallaro|first3=L.|last4=Cancelliere|first4=A.|last5=Foti|first5=E.|date=2015-10-01|title=Significant wave height record extension by neural networks and reanalysis wind data|url=http://www.sciencedirect.com/science/article/pii/S1463500315001432|journal=Ocean Modelling|volume=94|pages=128–140|doi=10.1016/j.ocemod.2015.08.002|bibcode=2015OcMod..94..128P}}</ref><ref>{{Cite journal|last=Dwarakish|first=G. S.|last2=Rakshith|first2=Shetty|last3=Natesan|first3=Usha|date=2013|title=Review on Applications of Neural Network in Coastal Engineering|url=http://www.ciitresearch.org/dl/index.php/aiml/article/view/AIML072013007|journal=Artificial Intelligent Systems and Machine Learning|language=English|volume=5|issue=7|pages=324–331}}</ref> 和[https://en.wikipedia.org/wiki/Geomorphology 地貌学]<ref>{{Cite journal|last=Ermini|first=Leonardo|last2=Catani|first2=Filippo|last3=Casagli|first3=Nicola|date=2005-03-01|title=Artificial Neural Networks applied to landslide susceptibility assessment|url=http://www.sciencedirect.com/science/article/pii/S0169555X04002272|journal=Geomorphology|series=Geomorphological hazard and human impact in mountain environments|volume=66|issue=1|pages=327–343|doi=10.1016/j.geomorph.2004.09.025|bibcode=2005Geomo..66..327E}}</ref>只是其中很少的几个例子。

===模型的类型===

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~~许多类型的模型被使用，在不同级定义的抽象概念并建模神经系统的不同方面。他们包括从【个体神经元】~~<ref>{{cite journal | author=Forrest MD |title=Simulation of alcohol action upon a detailed Purkinje neuron model and a simpler surrogate model that runs >400 times faster |journal= BMC Neuroscience | volume=16 |issue=27 | date=April 2015 |doi=10.1186/s12868-015-0162-6 |url=http://www.biomedcentral.com/1471-2202/16/27 }}</ref>短期行为的模型，神经环路动力学如何从个体神经元交互中产生的模型，到行为如何从代表完整子系统的抽象神经模块中产生的模型。这些包括神经系统和它们与从个体神经元到系统层面学习、记忆的关系的长期，短期可塑性模型。

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许多类型的模型被使用，在不同级定义的抽象概念并建模神经系统的不同方面。他们包括从[https://en.wikipedia.org/wiki/Biological_neuron_models 个体神经元]<ref>{{cite journal | author=Forrest MD |title=Simulation of alcohol action upon a detailed Purkinje neuron model and a simpler surrogate model that runs >400 times faster |journal= BMC Neuroscience | volume=16 |issue=27 | date=April 2015 |doi=10.1186/s12868-015-0162-6 |url=http://www.biomedcentral.com/1471-2202/16/27 }}</ref>短期行为的模型，神经环路动力学如何从个体神经元交互中产生的模型，到行为如何从代表完整子系统的抽象神经模块中产生的模型。这些包括神经系统和它们与从个体神经元到系统层面学习、记忆的关系的长期，短期可塑性模型。

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==理论性质（Theoretical properties）==

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