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6篇 您的检索式：作者名="Halit G"

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		题名	作者	年代	出处	被引量
	1	Credit Default Swap Spread and Succession Events显示文摘	Halit G Floris S Willem PFA	2007	Journal of Financial Regulation and Compli- ance2007，15，4：	1
	2	Second-line gemcitabine-based chemotherapy regimens improve overall 3-year survival rate in patients with malignant pleural mesothelioma: a multicenter retrospective study显示文摘	Hasan Mutlu ?eyda Gündüz Halit Karaca Abdullah Büyük?elik Yasemin Benderli Cihan Abdülsamet Erden Zeki Akca Hasan ?enol Co?kun	2014	Medical Oncology2014，，8：	1
	3	Effects of Particle Shape and Size Distributions on the Electrical and Magne- tic Properties of Niekel/Polyethylene Composites 显示文摘	S G Halit J F Thomas D M Kalyon	1993	Journal of Applied Polymer Science1993，50，：	1
	4	Effects of particle shape and size distributions on the electrical and magnetic properties of nickel/polyethylene composites 显示文摘	Halit S G Thomas J F Dilhan M K	1993	Appl Polym Sci1993，50，11：	1
	5	Effects of particle shape and size distributions on the electrical and magnetic properties of nickel/polyethylene composites显示文摘	Halit S G Thomas J F Kalyon D M	1993	Journal of Applied Polymer Science1993，50，11：	1
	6	Cylinder Pressure Prediction of An HCCI Engine Using Deep Learning显示文摘Engine tests are both costly and time consuming in developing a new internal combustion engine.Therefore,it is of great importance to predict engine characteristics with high accuracy using artificial intelligence.Thus,it is possible to reduce engine testing costs and speed up the engine development process.Deep Learning is an effective artificial intelligence method that shows high performance in many research areas through its ability to learn high-level hidden features in data samples.The present paper describes a method to predict the cylinder pressure of a Homogeneous Charge Compression Ignition(HCCI)engine for various excess air coefficients by using Deep Neural Network,which is one of the Deep Learning methods and is based on the Artificial Neural Network(ANN).The Deep Learning results were compared with the ANN and experimental results.The results show that the difference between experimental and the Deep Neural Network(DNN)results were less than 1%.The best results were obtained by Deep Learning method.The cylinder pressure was predicted with a maximum accuracy of 97.83%of the experimental value by using ANN.On the other hand,the accuracy value was increased up to 99.84%using DNN.These results show that the DNN method can be used effectively to predict cylinder pressures of internal combustion engines.	Halit Yaşar GültekinÇağıl Orhan Torkul MerveŞişci	2021	Chinese Journal of Mechanical Engineering2021，34，2：	0

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