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| 1 | Direct and indirect energy requirements of household in India显示文摘 | Pachauri S Spreng D | | 0，，6： | 1 |
| 2 | The Household Energy Transition in India and China显示文摘 | Pachauri S Jiang L | 2008 | Energy Policy2008，36，11： | 1 |
| 3 | Chelation in metalintoxication显示文摘 | FLORA S J PACHAURI V | 2010 | Int J Environ Res Public Health2010，7，7： | 1 |
| 4 | Urban and rural energy use and carbon dioxide emissions in Asia显示文摘 | Volker Krey Brian C. O’Neill Bas van Ruijven Vaibhav Chaturvedi Vassilis Daioglou Jiyong Eom Leiwen Jiang Yu Nagai Shonali Pachauri Xiaolin Ren | 2012 | Energy Economics2012，，： | 1 |
| 5 | Direct and indirect energy requirements of households in India显示文摘 | Shonali Pachauri Daniel Spreng | 2002 | Energy Policy2002，30，6： | 1 |
| 6 | Direct and indirect energy requirements of households in India显示文摘 | Shonali Pachauri Daniel Sperng | 2002 | Energy Policy2002，30，： | 1 |
| 7 | Determination enzyme Nacetyle-β-D-glucosaminidase activity for screeing dairy herds for mastitis显示文摘 | Nauriyal D S Pachauri S S | 1999 | Indian Journal of Animal Sciences1999，69，3： | 1 |
| 8 | Arsenic induced neuronal apoptosis in guinea pigs is Ca2+dependent and abrogated by chelation therapy:role of voltage gated calcium channels显示文摘 | PACHAURI V MEHTA A MISHRA D | 2013 | Neurotoxicology2013，35，： | 1 |
| 9 | Arsenic induced neuronal apoptosis in guinea pigs is Ca2+dependent and abrogated by chelation therapy:role of voltage gated calcium channels显示文摘 | PACHAURI V MEHTA A MISHRA D | 2013 | Neurotoxicology2013，35，： | 1 |
| 10 | Direct and indirect energy requirements of households in India显示文摘 | Pachauri S Spreng D | | 0，，30： | 1 |
| 11 | Preparation and char-acterization of monensin loaded PLGA nanoparticles:in vitro anti-malarial activity against plasmodium falciparum显示文摘 | Surolia R Pachauri M Ghosh PC | 2012 | J Biomed Nanotechnol2012，8，1： | 1 |
| 12 | The household energy transition in India and China显示文摘 | Shonali Pachauri Leiwen Jiang | 2008 | Energy Policy2008，36，11： | 1 |
| 13 | The Household Energy Transition in India and China 显示文摘 | Shonali Pachauri Leiwen Jiang | 2008 | Energy Policy2008，36，： | 1 |
| 14 | MiADMSA protects arsenic-induced oxidative stress in human keratinocyte HaCaT cells显示文摘 | Pachauri V Srivastava P Yadav A | 2013 | Biol Trace Elem Res2013，153，13： | 1 |
| 15 | Direct and indirect energy requirements of household in India显示文摘 | Pachauri S Spreng D | 2002 | Energy Policy2002，，30： | 1 |
| 16 | Enhancing the relevance of Shared Socioeconomic Pathways for climate change impacts, adaptation and vulnerability research显示文摘 | Bas J. Ruijven Marc A. Levy Arun Agrawal Frank Biermann Joern Birkmann Timothy R. Carter Kristie L. Ebi Matthias Garschagen Bryan Jones Roger Jones Eric Kemp-Benedict Marcel Kok Kasper Kok Maria Carmen Lemos Paul L. Lucas Ben Orlove Shonali Pachauri Tom M | 2014 | Climatic Change2014，，3： | 1 |
| 17 | High resolution 2D electrical resistivity tomography to characterize active Naitwar Bazar landslide, Garhwal Himalaya, India显示文摘 | MONDAL S K SASTRY R G PACHAURI A K | 2008 | Current Science2008，94，7： | 1 |
| 18 | A comparative multivariate analysis of household energy requirements in Australia, Brazil, Denmark, India and Japan显示文摘 | M Wier M Cohen C Hayami H Pachauri S Sehae- ffer R | 2006 | ENERGY2006，31，23： | 1 |
| 19 | Regression tree ensemble learning-based prediction of the heating and cooling loads of residential buildings显示文摘Building energy consumption is heavily dependent on its heating load(HL)and cooling load(CL).Therefore,an efficient building demand forecast is critical for ensuring energy savings and improving the operating efficacy of the heating,ventilation,and air conditioning(HVAC)system.Modern and specialized energy-efficient building modeling technologies may offer a fair estimate of the influence of different construction methods.However,deploying these tools could be time-consuming and complex for the user.Thus,in this article,an ensemble model based on decision trees and the least square-boosting(LS-boosting)algorithm known as the regression tree ensemble(RTE)is proposed for the accurate prediction of HL and CL.The hyper parameters of the RTE are optimized by shuffled frog leaping optimization(SFLA),which leads to SRTE.Stepwise regression(STR)and Gaussian process regression(GPR)based on different kernel functions are also designed for comparison purposes.Results demonstrate that the value of root mean squared error is reduced by 37%–68%and 30%–41%for HL and CL of residential buildings,respectively,by the proposed SRTE in comparison to other models.Furthermore,the findings from the real dataset support the proposed model’s effectiveness in predicting HVAC energy usage.It can be concluded that the proposed SRTE is more effective and accurate than other methods for predicting the energy consumption of HVAC systems. | Nikhil Pachauri Chang Wook Ahn | 2022 | Building Simulation2022，15，11： | 1 |
| 20 | Alternate indige-nous therapy for bovine mastitis显示文摘 | Pachauri S P Rajora V R Gupta G C | 1999 | Indian Vet Med J1999，23，3： | 1 |
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