{"currentpage":1,"firstResult":0,"maxresult":10,"pagecode":5,"pageindex":{"endPagecode":5,"startPagecode":1},"records":[{"abstractinfo":"简略介绍了<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>的基本思想及特点,综述了<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>在材料性能预测、工艺参数优化、相变规律的研究、微观组织模拟等领域的应用情况.对<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>研究中存在的问题进行了分析,展望了其应用前景.","authors":[{"authorName":"赖静","id":"789d1363-8cb1-457c-81ba-3257d59af78e","originalAuthorName":"赖静"},{"authorName":"王清","id":"2e44c95e-e141-49af-8b16-58af159b2aa5","originalAuthorName":"王清"},{"authorName":"孙东立","id":"99381c44-1bc5-42e7-89b3-757de8f825b7","originalAuthorName":"孙东立"}],"doi":"10.3969/j.issn.1001-4381.2006.z1.121","fpage":"458","id":"7f0a71a9-ab61-4bdb-9299-44d9808aa7e5","issue":"z1","journal":{"abbrevTitle":"CLGC","coverImgSrc":"journal/img/cover/CLGC.jpg","id":"9","issnPpub":"1001-4381","publisherId":"CLGC","title":"材料工程"},"keywords":[{"id":"c117048d-1982-4342-9138-0137871b3a85","keyword":"<span style=\"color:red\">人工</span><span 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style=\"color:red\">神经网络</span>将在炼钢生产过程中得到广泛的应用.","authors":[{"authorName":"王登峰","id":"33892757-755e-4d9b-863a-6e2f2f9395a8","originalAuthorName":"王登峰"},{"authorName":"倪红卫","id":"e60e0d3c-11e0-4868-a8a0-f17e6cd559fb","originalAuthorName":"倪红卫"}],"doi":"10.3969/j.issn.1001-1447.2005.02.008","fpage":"27","id":"d958fb48-ff5a-4f9e-888d-7c69deebe2c0","issue":"2","journal":{"abbrevTitle":"GTYJ","coverImgSrc":"journal/img/cover/GTYJ.jpg","id":"29","issnPpub":"1001-1447","publisherId":"GTYJ","title":"钢铁研究"},"keywords":[{"id":"b07a31af-15bb-4e41-8fb3-363ba88f1346","keyword":"转炉炼钢","originalKeyword":"转炉炼钢"},{"id":"e6b58d06-a59f-4d84-89e3-7ff3f8d0659f","keyword":"<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>","originalKeyword":"人工神经网络"},{"id":"535aa5a0-06ce-4338-b11e-ff8e23140895","keyword":"终点预报","originalKeyword":"终点预报"},{"id":"f5670002-ccbd-4cab-bb08-530e38571920","keyword":"命中率","originalKeyword":"命中率"}],"language":"zh","publisherId":"gtyj200502008","title":"<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>在转炉炼钢终点预报中的应用研究","volume":"33","year":"2005"},{"abstractinfo":"无缝钢管张力减径是多机架机组对荒管进行无芯棒连轧过程.它具有复杂的金属流动状态,影响其精度的工艺参数较多,难以用现有轧制理论进行分析.应用<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>的BP算法,对不同坯料样本进行训练学习,确定其权值和阈值,建立起预测管材精度的数学模型.经试验证明该模型具有较高的可靠性和精度.","authors":[{"authorName":"双远华","id":"2f84a9c5-0bbb-4ef0-80a3-7ab3170e498b","originalAuthorName":"双远华"},{"authorName":"樊建成","id":"ad7d8407-3420-47b2-8484-db9d1b713bbe","originalAuthorName":"樊建成"},{"authorName":"赖明道","id":"e725f02b-d891-4e30-9869-1529ba868da1","originalAuthorName":"赖明道"}],"doi":"","fpage":"28","id":"c0c479af-6df7-407e-b20b-30138cde6c5a","issue":"2","journal":{"abbrevTitle":"GT","coverImgSrc":"journal/img/cover/GT.jpg","id":"27","issnPpub":"0449-749X","publisherId":"GT","title":"钢铁"},"keywords":[{"id":"9ddb8c99-faf0-4862-8c6c-3a6e92d77455","keyword":"张力减径","originalKeyword":"张力减径"},{"id":"16120877-6748-41d9-9ef6-0cea4dbfd0c5","keyword":"<span 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style=\"color:red\">神经网络</span>在材料设计、材料加工的智能控制、材料相变研究和材料性能预测等方面的应用.","authors":[{"authorName":"樊新民","id":"dc1fbe16-cf9c-40de-a1cf-8a29b3fb5b91","originalAuthorName":"樊新民"},{"authorName":"孔见","id":"e8937561-6896-4707-9244-da231739a6f2","originalAuthorName":"孔见"},{"authorName":"金波","id":"5ee7179a-0f32-4728-910b-0c0190d2d91c","originalAuthorName":"金波"}],"doi":"","fpage":"28","id":"54f03110-04cf-483f-96af-c89e66fdb854","issue":"4","journal":{"abbrevTitle":"CLDB","coverImgSrc":"journal/img/cover/CLDB.jpg","id":"8","issnPpub":"1005-023X","publisherId":"CLDB","title":"材料导报"},"keywords":[{"id":"3356809b-0e13-4324-99a6-40bddfd47340","keyword":"<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>","originalKeyword":"人工神经网络"},{"id":"58dce7e4-712a-4f5b-9bd0-94fde366eb5d","keyword":"材料科学","originalKeyword":"材料科学"},{"id":"76424353-af59-46c5-a2ab-d84bbd8b55fc","keyword":"计算机应用","originalKeyword":"计算机应用"}],"language":"zh","publisherId":"cldb200204008","title":"<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>在材料科学研究中的应用","volume":"16","year":"2002"},{"abstractinfo":"介绍了<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>在炼钢生产上的应用,指出利用<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>原理建立预报模型是一种容错性好、通用性强的可靠预报方法.","authors":[{"authorName":"吕俊杰","id":"24e4642b-20fa-4595-b6e9-44071ce18061","originalAuthorName":"吕俊杰"},{"authorName":"雷亚","id":"811c31e2-1302-4d6b-ab7a-7f6e96257648","originalAuthorName":"雷亚"}],"doi":"10.3969/j.issn.1006-9356.2004.06.008","fpage":"34","id":"b738e092-fb61-4538-bde6-2b08613518b8","issue":"6","journal":{"abbrevTitle":"ZGYJ","coverImgSrc":"journal/img/cover/ZGYJ.jpg","id":"87","issnPpub":"1006-9356","publisherId":"ZGYJ","title":"中国冶金"},"keywords":[{"id":"0466a577-4879-49a3-b1d3-48a9766a8753","keyword":"<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>","originalKeyword":"人工神经网络"},{"id":"28e14dd5-6a1b-4cfd-be16-099d31bd2c11","keyword":"炼钢","originalKeyword":"炼钢"},{"id":"0013d5e3-14e0-4647-99e6-27a9f070c1a1","keyword":"预报模型","originalKeyword":"预报模型"}],"language":"zh","publisherId":"zgyj200406008","title":"<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>在炼钢生产上的应用","volume":"","year":"2004"},{"abstractinfo":"选取了几种常用的金属氧化物掺杂剂,在均匀实验结构的基础上用<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>方法对掺杂PZT陶瓷的性能进行分析和优化.实验结果表明,掺杂PZT体系的<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>模型要比多重非线形回归模型准确得多,而且以<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>模型为指导对材料进行优化后的性能预测也比较准确,说明<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>在陶瓷这种多组分固溶体材料的性能分析中具有良好的使用前景.","authors":[{"authorName":"郭栋","id":"b2042f37-bdf7-4811-8c62-989fcf0aa1f7","originalAuthorName":"郭栋"},{"authorName":"齐西伟","id":"12af3be6-c565-4c6b-b092-0cff0fbaa77c","originalAuthorName":"齐西伟"},{"authorName":"李龙土","id":"b4fb0d8b-271f-4ec7-95cc-747a44ff17fe","originalAuthorName":"李龙土"},{"authorName":"南策文","id":"0feb07af-45d9-4d2f-9e9f-5fc57abb4204","originalAuthorName":"南策文"},{"authorName":"桂治轮","id":"2b63c4a8-d3d4-48ab-8874-20aa14add85e","originalAuthorName":"桂治轮"}],"doi":"10.3321/j.issn:1000-324X.2004.01.036","fpage":"223","id":"361995be-18fe-413a-9ea1-8b1231ac7ae5","issue":"1","journal":{"abbrevTitle":"WJCLXB","coverImgSrc":"journal/img/cover/WJCLXB.jpg","id":"62","issnPpub":"1000-324X","publisherId":"WJCLXB","title":"无机材料学报"},"keywords":[{"id":"50ad7a71-5e97-400e-a69f-21dd14fc9e2d","keyword":"压电陶瓷","originalKeyword":"压电陶瓷"},{"id":"26f3352b-222b-4f2f-88d1-fabb85a95ad3","keyword":"<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>","originalKeyword":"人工神经网络"},{"id":"0eca7d23-45dd-43dd-b103-2118b5fd6278","keyword":"误差反向传播算法","originalKeyword":"误差反向传播算法"},{"id":"ea0fb2b1-484a-47b1-ac8c-3486e329e6cf","keyword":"电学性能","originalKeyword":"电学性能"}],"language":"zh","publisherId":"wjclxb200401036","title":"用<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>对PZT陶瓷进行性能分析与优化","volume":"19","year":"2004"},{"abstractinfo":"采用<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>技术建立了碳钢、低合金钢大气腐蚀预测模型,<span style=\"color:red\">神经网络</span>拓朴结构为13-19-1,<span style=\"color:red\">神经网络</span>模型预测结果和实验数据紧密相符,而且通过单一因素敏感性分析方法,研究了合金元素和环境因素对于大气腐蚀速率的影响,表明该方法的有效性.","authors":[{"authorName":"王海涛","id":"f27aeb1e-aa3a-4d9c-ac07-bcefabac34b5","originalAuthorName":"王海涛"},{"authorName":"韩恩厚","id":"484eb7f0-5df8-4c69-a380-a1bdbcf10ae3","originalAuthorName":"韩恩厚"},{"authorName":"柯伟","id":"ad9abf90-5aec-4450-885c-3c591f0615e1","originalAuthorName":"柯伟"}],"doi":"10.3969/j.issn.1002-6495.2006.02.019","fpage":"144","id":"782a26bf-28ae-4b83-9040-8d67adaad84b","issue":"2","journal":{"abbrevTitle":"FSXB","coverImgSrc":"journal/img/cover/腐蚀学报封面.jpg","id":"24","issnPpub":"2667-2669","publisherId":"FSXB","title":"腐蚀学报（英文）"},"keywords":[{"id":"05dcfeea-152c-4c4b-be88-9df8e3a43ca3","keyword":"<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>","originalKeyword":"人工神经网络"},{"id":"fa5c6a6c-5453-4e03-9e44-7b8c711002d7","keyword":"大气腐蚀","originalKeyword":"大气腐蚀"},{"id":"7fc79934-131c-458b-a9c5-8847d7d8c516","keyword":"模型","originalKeyword":"模型"},{"id":"24c10c75-4a64-4179-bd9c-2b80c522b07a","keyword":"敏感性分析","originalKeyword":"敏感性分析"}],"language":"zh","publisherId":"fskxyfhjs200602019","title":"用<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>构建碳钢、低合金钢大气腐蚀模型","volume":"18","year":"2006"},{"abstractinfo":"<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>技术广泛应用于复杂系统的建模中,已成为材料科学研究中常用的建模方法.介绍了BP<span style=\"color:red\">神经网络</span>及其建模的重要特征,综述了<span style=\"color:red\">神经网络</span>技术在材料性能预测方面的研究情况.","authors":[{"authorName":"徐文峰","id":"b3a98bff-3461-4651-b13f-2267a8b907a3","originalAuthorName":"徐文峰"},{"authorName":"廖晓玲","id":"796e55fc-5f39-41a4-8c2d-de3e39a51c07","originalAuthorName":"廖晓玲"},{"authorName":"刘希东","id":"ab48b26e-f912-44ec-aac7-3596e9768638","originalAuthorName":"刘希东"}],"doi":"","fpage":"237","id":"77f6e950-edcf-4b89-ad86-409ffc906bc7","issue":"z2","journal":{"abbrevTitle":"CLDB","coverImgSrc":"journal/img/cover/CLDB.jpg","id":"8","issnPpub":"1005-023X","publisherId":"CLDB","title":"材料导报"},"keywords":[{"id":"8d81d008-91dd-4770-af84-fb982c1a4f6c","keyword":"材料","originalKeyword":"材料"},{"id":"7855dfa4-5c3f-4e9e-8feb-e298c56cd878","keyword":"<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>","originalKeyword":"人工神经网络"},{"id":"1a558ea5-2971-44e7-867f-f6d7bbc6ea3b","keyword":"性能","originalKeyword":"性能"}],"language":"zh","publisherId":"cldb2006z2070","title":"<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>在材料性能研究中的应用","volume":"20","year":"2006"},{"abstractinfo":"<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>具有非线性的自适应信息处理能力,已广泛应用于化工、通信、控制及优化等领域.在简单介绍<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>方法的基础上,重点综述了该方法在陶瓷工业的原料分类、配方优化、缺陷分析、性能预测等方面的应用情况,指出在应用过程中可能存在的问题以及未来的发展趋势.","authors":[{"authorName":"黄国兴","id":"d53002c5-20aa-45be-8fe4-4bb4b74b0514","originalAuthorName":"黄国兴"},{"authorName":"李琳","id":"023e861b-59b8-4a52-a7d5-0acc2b2c64ae","originalAuthorName":"李琳"},{"authorName":"李冰","id":"0bea6499-c118-4676-b3be-8341ef1acac5","originalAuthorName":"李冰"},{"authorName":"陈玲","id":"e43c3d26-4edf-4a44-b85a-239afabcbfe8","originalAuthorName":"陈玲"},{"authorName":"李坚斌","id":"92bb10b6-a84a-4702-8c9e-f0e6c34909d2","originalAuthorName":"李坚斌"}],"doi":"","fpage":"80","id":"1da8e30c-dad7-45e3-87a8-6f6262ac8dbc","issue":"11","journal":{"abbrevTitle":"CLDB","coverImgSrc":"journal/img/cover/CLDB.jpg","id":"8","issnPpub":"1005-023X","publisherId":"CLDB","title":"材料导报"},"keywords":[{"id":"7af1ee4b-38a9-4634-a9fd-04bd5ce5d437","keyword":"<span style=\"color:red\">人工</span><span 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style=\"color:red\">神经网络</span>方法预测高碳钢高速线材产品力学性能,将预报结果与试验结果相比较可知,该模型具有较高的精度.","authors":[{"authorName":"芮小艳","id":"64e3af4a-7eda-40bc-a99a-7d56afa4aecc","originalAuthorName":"芮小艳"}],"doi":"10.3969/j.issn.1001-1447.2000.05.009","fpage":"29","id":"557913a2-d2de-4d8d-b5cf-044c90a33257","issue":"5","journal":{"abbrevTitle":"GTYJ","coverImgSrc":"journal/img/cover/GTYJ.jpg","id":"29","issnPpub":"1001-1447","publisherId":"GTYJ","title":"钢铁研究"},"keywords":[{"id":"2fee5509-16cd-4a39-9ffa-6598789d25f6","keyword":"<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>","originalKeyword":"人工神经网络"},{"id":"8023a492-3070-4df0-8666-04d486e8078d","keyword":"控制冷却","originalKeyword":"控制冷却"},{"id":"72945fa9-f513-4442-a347-aa973d2c9f4f","keyword":"高碳钢","originalKeyword":"高碳钢"},{"id":"91e5f402-5fa7-47ed-9fc2-f1ae9d541a40","keyword":"高速线材","originalKeyword":"高速线材"}],"language":"zh","publisherId":"gtyj200005009","title":"用<span style=\"color:red\">人工</span><span style=\"color:red\">神经网络</span>模型预测高碳钢高速线材力学性能","volume":"","year":"2000"}],"totalpage":432,"totalrecord":4312}