Results 21 to 30 of about 82,724 (185)

GEP-DNN4Mol: automatic chemical molecular design based on deep neural networks and gene expression programming

Health Information Science and Systems
The inverse design of molecules has attracted widespread attention in the field of chemical molecular design. However, existing methods fail to address the diversity of the generated molecules. In this work, we propose a molecule generation method called GEP-DNN4Mol to generate molecules with good diversity and desired properties in the exploration of ...
Wen Zheng, Zhong Li, Yuanyuan Chen, Wenjia Liao, Lei Deng, Hao Zhang, Yanmei Lin, Yuzhong Peng   +7 more
semanticscholar   +3 more sources

Predicting 28-day compressive strength of fibre-reinforced self-compacting concrete (FR-SCC) using MEP and GEP [PDF]

Scientific Reports
The utilization of Self-compacting Concrete (SCC) has escalated worldwide due to its superior properties in comparison to normal concrete such as compaction without vibration, increased flowability and segregation resistance.
Waleed Bin Inqiad, Muhammad Shahid Siddique, Mujahid Ali, Taoufik Najeh   +3 more
doaj   +2 more sources

Comparison of artificial neural networks (ANN), support vector machine (SVM) and gene expression programming (GEP) approaches for predicting TBM penetration rate

SN Applied Sciences, 2020
Alireza Afradi, Arash Ebrahimabadi, Afradi Alireza   +2 more
exaly   +2 more sources

Yarn Strength Modelling Using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Gene Expression Programming (GEP)

Journal of Engineered Fibers and Fabrics, 2013
This study compares capabilities of two different modelling methodologies for predicting breaking strength of rotor spun yarns. Forty eight yarn samples were produced considering variations in three drawing frame parameters namely break draft, delivery speed, and distance between back and middle rolls.
Alireza Fallahpour, A. Moghassem
semanticscholar   +2 more sources

Modeling mechanical properties of rubberized concrete using gene expression programming (GEP) and random forest: a comparative study. [PDF]

Sci Rep
Sheraz M, Talha M, Alam M, Farhan M, Ul Haq Z, Rashid M, Alabduljabbar H, Ahmad F.   +7 more
europepmc   +3 more sources

Comparative study of genetic programming-based algorithms for predicting the compressive strength of concrete at elevated temperature

Case Studies in Construction Materials, 2023
The elevated temperature severely influences the mixed properties of concrete, causing a decrease in its strength properties. Accurate proportioning of concrete components for obtaining the required compressive strength (C-S) at elevated temperatures is ...
Abdulaziz Alaskar, Ghasan Alfalah, Fadi Althoey, Mohammed Awad Abuhussain, Muhammad Faisal Javed, Ahmed Farouk Deifalla, Nivin A. Ghamry   +6 more
doaj   +1 more source

Prediction of Blast-Induced Ground Vibration Using Gene Expression Programming (GEP), Artificial Neural Networks (ANNs), and Linear Multivariate Regression (LMR)

Archives of Mining Sciences, 2023
In this paper, an attempt was made to find out two empirical relationships incorporating linear mul- tivariate regression (LMR) and gene expression programming (GEP) for predicting the blast-induced ground vibration (BIGV) at the Sarcheshmeh copper mine ...
Jamshid Shakeri, B. J. Shokri, Hesam Dehghani   +2 more
semanticscholar   +1 more source

Prediction of blast-induced air overpressure using a hybrid machine learning model and gene expression programming (GEP): A case study from an iron ore mine

AIMS Geosciences, 2023
Mine blasting can have a destructive effect on the environment. Among these effects, air overpressure (AOp) is a major concern. Therefore, a careful assessment of the AOp intensity should be conducted before any blasting operation in order to minimize ...
Mohammad Kazemi, Zohreh Nabavi, M. Khandelwal   +2 more
semanticscholar   +1 more source

Distributed Function Mining for Gene Expression Programming Based on Fast Reduction. [PDF]

PLoS ONE, 2016
For high-dimensional and massive data sets, traditional centralized gene expression programming (GEP) or improved algorithms lead to increased run-time and decreased prediction accuracy. To solve this problem, this paper proposes a new improved algorithm
Song Deng, Dong Yue, Le-chan Yang, Xiong Fu, Ya-zhou Feng   +4 more
doaj   +1 more source

Artificial Intelligence-Based Image Classification Techniques for Hydrologic Applications

Applied Artificial Intelligence, 2022
Hydrologic modeling is a complex phenomenon dependent on numerous parameters. Since the estimation of parameters is subjected to high uncertainty due to high spatial variation.
Ritica Thakur, V. L. Manekar
doaj   +1 more source