Manoj Khandelwal

Ocean Engineering · 2010–2021

A researcher in the Science corpus: 6 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Ocean Engineering — 13 citations into it
• Mechanics of Materials — 12 citations into it
• Artificial Intelligence — 11 citations into it
• Statistics and Probability — 5 citations into it

Whom Manoj Khandelwal trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Jian Zhou
2. Jerome H. Friedman

Who trusts Manoj Khandelwal overall

1. Mohammad Esmaeili
2. A. Salimi

Papers from Manoj Khandelwal's perspective

Ordered by how strongly the researchers Manoj Khandelwal trusts endorse each paper. Same corpus, a different order for every researcher.

1. A Taxonomy of Global Optimization Methods Based on Response Surfaces
2. Classification of Rockburst in Underground Projects: Comparison of Ten Supervised Learning Methods (Journal of computing in civil engineering)
3. Blasting-induced flyrock and ground vibration prediction through an expert artificial neural network based on particle swarm optimization (Arabian Journal of Geosciences)
4. Assessment of shallow landslide susceptibility using artificial neural networks in Jabonosa River Basin, Venezuela
5. Estimation of the TBM advance rate under hard rock conditions using XGBoost and Bayesian optimization
6. Optimization of support vector machine through the use of metaheuristic algorithms in forecasting TBM advance rate (Engineering applications of artificial intelligence)
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. Regression Shrinkage and Selection via the Lasso
9. ImageNet classification with deep convolutional neural networks
10. The Nature of Statistical Learning Theory

Their papers

• Proposing a novel comprehensive evaluation model for the coal burst liability in underground coal mines considering uncertainty factors (2021) — 104 citations
• Performance evaluation of hybrid WOA-XGBoost, GWO-XGBoost and BO-XGBoost models to predict blast-induced ground vibration (2021) — 447 citations
• Stability prediction of Himalayan residual soil slope using artificial neural network (2020) — 79 citations
• Estimation of the TBM advance rate under hard rock conditions using XGBoost and Bayesian optimization (2020) — 240 citations
• Evaluation and prediction of blast induced ground vibration using support vector machine (2010) — 148 citations
• Prediction of macerals contents of Indian coals from proximate and ultimate analyses using artificial neural networks (2010) — 56 citations