An explosion in high-resolution ion channel structures paved way for structure-based rational drug design and the state-of-the-art simulation and machine learning techniques dramatically improved the efficiency and effectiveness of computer-aided drug design. Here we present an overview of how ...
We developed a simulation methodology on the basis of machine learning techniques for simulation of pharmaceutical solubility in a supercritical solvent, i.e., CO2 with the perspective of nanodrug production. The X variables considered in this simulation work included pressure and temperature of the ...
Monostori, L., Kadar, B., Viharos, Zs.J., Mezgar, I., Stefan, P., 2000, Combined use of simulation and AI/machine learning techniques in designing manufacturing processes and systems, Proc. of the 2000 International CIRP Design Seminar, Haifa, Israel, May 16-18:199-204....
Advanced machine learning techniques for building performance simulation: a comparative analysismachine learningenergy modellingXGBoostartificial neural networksfeature engineeringfeature selectionEnergy consumption predictions for buildings play an important role in energy efficiency and sustainability research. Accurate...
Machine learning techniques for propensity score matching with clustered data . A simulation study . 来自 Semantic Scholar 喜欢 0 阅读量: 65 作者:A Bruno,C Massimo 摘要: Propensity score method is a classic tool for obtaining causal estimates from non-randomized data. In the applied literature ...
The role and potential of Machine Learning (ML) were central parts of both articles. This has led us to the conclusion that we should properly investigate and digest what companies are currently using these data-based techniques for. To this end, we have looked at the extended abstracts, ...
Heterogeneous catalysis is at the heart of chemistry. New theoretical methods based on machine learning (ML) techniques that emerged in recent years provide a new avenue to disclose the structures and reaction in complex catalytic systems. Here we review
For instance, machine learning techniques have been used to predict association rate constants based on the chemical or structural properties of proteins37,38. Physics-based methods, such as Brownian dynamic (BD) simulation, are widely used to reproduce the association of two proteins39–60. These...
This study not only enhances our understanding of the performance of dimensionality reduction on the microstructure evolution, but it also provides insights on strategies for accelerating phase-field modeling via machine learning techniques. 04 文章标题:模拟熔融盐热物理特性的计算方法 期刊名称:Communications...
radiation absorption estimations utilizing AI algorithms can ultimately replace traditional approaches and time-consuming large-scale energy estimates. The ANN methodology outperforms other machine learning techniques in predicting the objective function, which contains the amount of solar radiation absorption, ...