IERI Procedia最新文献_第3页

Ecological Effect of Multi-walled Carbon Nanotubes on Marine Microalgae Pseudo-Nitzschia Pungens and Isochrysis Galbana 多壁碳纳米管对海洋微藻pseudonitzschia Pungens和Galbana等chrysis的生态效应

IERI Procedia Pub Date : 2014-01-01 Epub Date: 2014-09-26 DOI: 10.1016/j.ieri.2014.09.021

K.S. Golokhvast , V.L. Kuznetsov , V.V. Chaika , S.A. Razgonova , T.Yu. Orlova

引用次数: 3

Challenges for Future of Natural Spaces of Canary Islands, Spain 西班牙加那利群岛自然空间未来的挑战

IERI Procedia Pub Date : 2014-01-01 Epub Date: 2014-09-26 DOI: 10.1016/j.ieri.2014.09.029

Juan C. Santamarta , Jorge Naranjo , M. Paz Arraiza

引用次数: 4

Hidden Markov Random Fields and Swarm Particles: A Winning Combination in Image Segmentation 隐马尔可夫随机场和群粒子:图像分割的成功组合

IERI Procedia Pub Date : 2014-01-01 Epub Date: 2014-10-01 DOI: 10.1016/j.ieri.2014.09.065

El-Hachemi Guerrout, Ramdane Mahiou, Samy Ait-Aoudia

引用次数: 16

Human-robot Communication for Surveillance of Elderly People in Remote Distance 基于人机通信的老年人远程监控

IERI Procedia Pub Date : 2014-01-01 Epub Date: 2014-10-01 DOI: 10.1016/j.ieri.2014.09.096

Shin-ichiro Kaneko , Genci Capi

引用次数: 5

The Application of PFZSSB in Advanced Wastewater Treatment from Landfill Leachate PFZSSB在垃圾渗滤液深度处理中的应用

IERI Procedia Pub Date : 2014-01-01 Epub Date: 2014-09-26 DOI: 10.1016/j.ieri.2014.09.042

Suqin Li , Suzhen Fang , Sai He , Yingjun Hao , Guohong Xiong

引用次数: 2

Suitability of KNN Regression in the Development of Interaction based Software Fault Prediction Models KNN回归在基于交互的软件故障预测模型开发中的适用性

IERI Procedia Pub Date : 2014-01-01 Epub Date: 2014-06-07 DOI: 10.1016/j.ieri.2014.03.004

Rinkaj Goyal, Pravin Chandra, Yogesh Singh

{"title":"Suitability of KNN Regression in the Development of Interaction based Software Fault Prediction Models","authors":"Rinkaj Goyal, Pravin Chandra, Yogesh Singh","doi":"10.1016/j.ieri.2014.03.004","DOIUrl":"10.1016/j.ieri.2014.03.004","url":null,"abstract":"<div><p>Accurate fault prediction is an indispensable step, to the extent of being a critical activity in software engineering. In fault prediction model development research, combination of metrics significantly improves the prediction capability of the model, but it also gives rise to the issue of handling an increased number of predictors and evolved nonlinearity due to complex interaction among metrics.</p><p>Ordinary least square (OLS) based parametric regression techniques cannot effectively model such nonlinearity with a large number of predictors because the global parametric function to fit the data is not known beforehand. In our previous studies<span>[1]</span>, <span>[2]</span>, <span>[3]</span>, we showed the impact of interaction in the combined metrics approach of fault prediction and statistically established the simultaneous increment in the predictive accuracy of the model with interaction.</p><p>In this study we use K-Nearest Neighbor (KNN) regression as an example of nonparametric regression technique, otherwise well known for classification tasks in the data mining community. Through the results derived here, we empirically establish and validate the hypothesis that the performance of KNN regression remains ordinarily unaffected with increasing number of interacting predictors and simultaneously provides superior performance over widely used multiple linear regression (MLR).</p></div>","PeriodicalId":100649,"journal":{"name":"IERI Procedia","volume":"6 ","pages":"Pages 15-21"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.ieri.2014.03.004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81497334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 50

Towards Better Workflow Execution Time Estimation 迈向更好的工作流程执行时间估计

IERI Procedia Pub Date : 2014-01-01 Epub Date: 2014-10-01 DOI: 10.1016/j.ieri.2014.09.080

Artem M. Chirkin , Sergey V. Kovalchuk

引用次数: 15

Diameter Error Prediction Using Fuzzy Logic for Cast Nylon 6 Turning Operation 基于模糊逻辑的尼龙6车削加工直径误差预测

IERI Procedia Pub Date : 2014-01-01 Epub Date: 2014-10-01 DOI: 10.1016/j.ieri.2014.09.094

Bandit Suksawat

{"title":"Diameter Error Prediction Using Fuzzy Logic for Cast Nylon 6 Turning Operation","authors":"Bandit Suksawat","doi":"10.1016/j.ieri.2014.09.094","DOIUrl":"10.1016/j.ieri.2014.09.094","url":null,"abstract":"<div><p>A prediction model using fuzzy logic system for cast nylon 6 turning work piece diameter error forecasting was developed. The cutting parameters consisting of feed rate, depth of cut and cutting speed were determined as input variable of 75 fuzzy rules of input membership function. The diameter error values from 11 levels of fuzzy rules of output membership function were arranged as prediction outputs. Turning was carried out at 3 levels of turning speed and 5 levels feed rate then depths of cut were accomplished. Both experimental and predicted work piece diameter errors were used for validation. After that factors affecting on diameter error, precision and accuracy of the prediction values were statistically analyzed. The experimental results revealed that length of work piece and cutting speed did not effect on diameter error. However, depth of cut and feed rate affected on diameter error with total causal effect values at 0.6553 and 0.3085, respectively. Prediction of diameter error by the developed fuzzy system has an average absolute error at 0.535μm and R<sup>2</sup> at 0.988 compared with the experimental data. The precision of prediction was not significantly different from the experimental data at 95% of confidence interval. Therefore, the developed fuzzy system can predict diameter error in turning operation with high accuracy and precision.</p></div>","PeriodicalId":100649,"journal":{"name":"IERI Procedia","volume":"10 ","pages":"Pages 76-84"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.ieri.2014.09.094","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86611875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Evolution of Neural Controllers for Exploration of Dynamic Environments 用于动态环境探索的神经控制器的进化

IERI Procedia Pub Date : 2014-01-01 Epub Date: 2014-10-01 DOI: 10.1016/j.ieri.2014.09.095

MengZe Li, Genci Capi, Takayuki Oshima, Endri Rama

引用次数: 2

Geographical Feature based Research on Urban Color Environment – Taking Wuhan as an Example 基于地理特征的城市色彩环境研究——以武汉市为例

IERI Procedia Pub Date : 2014-01-01 Epub Date: 2014-09-26 DOI: 10.1016/j.ieri.2014.09.061

Shu Zhang, Yijie Liu, Hong Nie

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引用次数: 6