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| 1 | Compressive strength of cement stabilized fly ash-soil mixtures显示文摘 | Shenbaga R. Kaniraj Vasant G. Havanagi | 1999 | Cement and Concrete Research1999，，5： | 1 |
| 2 | Behavior of Cement-stabilized Fiber-reinforced Fly Ash-soil Mixtures显示文摘 | Kanirig and Vasant G Havanagi | 2001 | Journal of Geotechnical and Geoenvironmental Engineering2001，，2： | 1 |
| 3 | Geotechnical Behavior of Fly Ash Mixed with Randomly Oriented Fiber Inclusions显示文摘 | Shenbaga Kaniraj R Gayathri V | 2003 | Geotextiles and Geomembranes2003，21，： | 1 |
| 4 | An implementation of integer programming techniques in clustering algorithm显示文摘 | Shenbaga Ezhil S Dr C Vijayalakshmi | 2012 | Indian Journal of Computer Science and Engineering2012，3，1： | 1 |
| 5 | Aluminium-titani- um diboride (A1 Ti~ ) metal matrix composites:Chal- lenges and opportunities显示文摘 | SURESH S SHENBAGA V M N | 2012 | Proc Eng2012，38，： | 1 |
| 6 | Compres sive strength of cement stabilized flyash-soil mixtures 显示文摘 | Kaniraj Shenbaga R Havanagi Vasant G | 1999 | Cement and Concrete Research1999，29，1： | 1 |
| 7 | Variable compression ratio engine: A future power plant for automobiles-an overview显示文摘 | Amjad Shaik N Shenbaga Vinayaga Moorthi R Rudramoorthy | 2007 | Proceedings of the Institution of Mechanical Engineers Part D: Journal of Automobile Engineering2007，221，9： | 1 |
| 8 | Compressive Strength of Cement Stabilized Fly Ash-soil Mixtures显示文摘 | Shenbaga R K Vasant G H | 1999 | Cement and Concrete Research1999，29，： | 1 |
| 9 | Behavior of cement - stabilized fiber - reinforced fly ash - soil mixtures 显示文摘 | Shenbaga R Kanirig and Vasant G | 2001 | Journal of Geotechnical and Geoenvironmental Engineering2001，，7： | 1 |
| 10 | Prediction of Parkinson’s Disease Using Improved Radial Basis Function Neural Network显示文摘Parkinson’s disease is a neurogenerative disorder and it is difficult to diagnose as no therapies may slow down its progression.This paper contributes a novel analytic system for Parkinson’s Disease Prediction mechanism using Improved Radial Basis Function Neural Network(IRBFNN).Particle swarm optimization(PSO)with K-means is used to find the hidden neuron’s centers to improve the accuracy of IRBFNN.The performance of RBFNN is seriously affected by the centers of hidden neurons.Conventionally K-means was used to find the centers of hidden neurons.The problem of sensitiveness to the random initial centroid in K-means degrades the performance of RBFNN.Thus,a metaheuristic algorithm called PSO integrated with K-means alleviates initial random centroid and computes optimal centers for hidden neurons in IRBFNN.The IRBFNN uses Particle swarm optimization K-means to find the centers of hidden neurons and the PSO K-means was designed to evaluate the fitness measures such as Intracluster distance and Intercluster distance.Experimentation have been performed on three Parkinson’s datasets obtained from the UCI repository.The proposed IRBFNN is compared with other variations of RBFNN,conventional machine learning algorithms and other Parkinson’s Disease prediction algorithms.The proposed IRBFNN achieves an accuracy of 98.73%,98.47%and 99.03%for three Parkinson’s datasets taken for experimentation.The experimental results show that IRBFNN maximizes the accuracy in predicting Parkinson’s disease with minimum root mean square error. | Rajalakshmi Shenbaga Moorthy P.Pabitha | 2021 | Computers, Materials & Continua2021，，9： | 1 |
| 11 | Compressive strength of cement stabilized fly ash-soil mixtures显示文摘 | SHENBAGA R K VASANT G H | 1999 | Cement and Concrete Research1999，29，5： | 1 |
| 12 | Permeability and Consolidation Characteristics of Compacted Fly Ash 显示文摘 | Shenbaga R Kaniraj V Gayathri | 2004 | Journal of Energy Engineering2004，130，1： | 1 |
| 13 | Stability analysis of rein- forced embankments on soft soils 显示文摘 | Shenbaga R Kaniraj H A | 1992 | Journal of Geotechnieal Engineering1992，118，12： | 1 |
| 14 | Compressive Strength of Cement Stabilized Fly Ash--Soil Mixtures显示文摘 | Shenbaga R K Vasant G H | 1999 | Cement and Concrete Research1999，29，： | 1 |
| 15 | 软土地基上加筋路堤中加筋力方向的相关性显示文摘在对软土地基上加筋路堤进行旋转稳定分析的极限平衡方法中,假定加筋力作用于一特定方向,其所需的最大加筋力就可确定。通常假设该加筋力作用于水平方向(α=0),由此估计所需的最大加筋力值比较保守。已建议采用的另外两个作用方向是:破裂面与加筋层相交处的切线方向(α=θ);和该切线与水平面夹角的平分线方向(α=θ/2)。加筋力的这些作用方向直接影响着用于路堤加筋的规模和加筋层的选择。 本文论述了加筋力的作用方向对路堤加筋规模影响的研究成果。首先,求出了临界破裂面的位置和分别在α=θ/4及α=3θ/4两个方向上所需的最大加筋力值。用上述方法对其他不同的方向也得到合理的解,分析了两个路堤的实例。本文第二部分提出了分析的成果。同时,还推荐了选择α值的试验准则。 | Shenbaga R.Kaniraj 谭远发 | 1998 | 路基工程1998，，3： | 0 |
| 16 | 软土上路堤加固设计显示文摘软土对于建造在其上的路堤不能提供稳固的支撑,象采用土质改良之类的常规方法既费时间,也很不经济。最近,由于聚合材料的发展,在路堤基底铺设片状或网状聚合物进行加固,为增加其稳定性开辟了可供选择的新途径。对于这样的路基加固的设计,应该研究四种可能的破坏类型,即:承载力破坏、滑动破坏、地基土挤出破坏及转动破坏。设计主要是选择合理的路堤边坡坡度和考虑四种破坏形式均能保证安全的加固方法。本文对此问题进行了系统地探讨,并用一个例子作了说明。 | SHENBAGA R.KANIRAJ 张高宁 | 1990 | 路基工程1990，0，4： | 0 |
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