Soong, C.Y., Huang, W.T., Lin, F.P.: Chaos control on autonomous and non-autonomous systems with various types of genetic algorithm-optimized weak perturbations. Chaos Solitons Fractals 34 , 1519–1537 (2007)Soong, C.Y., Huang, W.T., Lin, F.P.: Chaos control on autonomous and ...
Based primarily on thetransformerdeep learning algorithm, large language models have been built on massive amounts of data to generate amazingly human-sounding language, as users ofChatGPTand interfaces of other LLMs know. They have become one of the most widely used forms of generative AI. Chat...
including exposure to toxic gases8,9,10, detergents11, infectious agents12, chemicals13,14, and genetic approaches13,15,16,17. The advantage of genetic approaches is that they allow the depletion of specific cell types without
including exposure to toxic gases8,9,10, detergents11, infectious agents12, chemicals13,14, and genetic approaches13,15,16,17. The advantage of genetic approaches is that they allow the depletion of specific cell types without
This research paper explores the concept of automating Monkey Testing by implementing a controlled variant, using genetic algorithms. It discusses the challenges, benefits, and limitations of automating and presents a genetic algorithm-based approach to achieve partial automation. “Automated Monkey Testing...
For the cost-effective optimization of well locations and types under geologic uncertainty, proxy modeling or surrogate modeling of reservoir simulation is required. Recently, a machine learning algorithm has been widely applied to predict reservoir responses and expedite an optimization. Since non-physics...
The parameters are calculated from the location and amplitudes of ECG fiducial points, determined with a new algorithm inspired by Pan-Tompkins's algorithm [14]. The classification results are satisfactory and better than contemporary methods introduced in the field....
genetic algorithmBack-propagation neural networkGenetic Algorithms (GAs) have a proven ability to improve the classification performance of Back-propagation Neural (BPN) networks by optimizing their topology and parameter settings. However, before they are used to optimize the BPN network, their ...
https://github.com/bulik/ldsc) to the GWAS summary statistics of the POAG cross-ancestry meta-analysis, POAG European subset meta-analysis, and IOP meta-analysis, and the four single-nucleus differential gene expression datasets described above, to evaluate the contribution of genetic variation in...
However, in clinical practice of genetic diagnosis using WES, different types of mutations and mechanisms should be considered simultaneously to identify the pathogenic mutation. With the development of machine learning (ML) and deep learning (DL), many computational methods using ML or DL have been...