[HTML][HTML] Ecosystem health risk assessment of lakes in the Inner Mongolian Plateau based on the coupled AHP-SOM-CGT model
L Zhao, R Ma, Z Yang, K Ning, P Chen, J Wu - Ecological Indicators, 2023 - Elsevier
The ecosystem health risk assessment of lake basins can provide a crucial foundation and
support for the sustainable development of ecosystems in the arid regions of northern China …
support for the sustainable development of ecosystems in the arid regions of northern China …
A modified Lanczos Algorithm for fast regularization of extreme learning machines
This paper presents a new regularization for Extreme Learning Machines (ELMs). ELMs are
Randomized Neural Networks (RNNs) that are known for their fast training speed and good …
Randomized Neural Networks (RNNs) that are known for their fast training speed and good …
[HTML][HTML] A dynamic annealing learning for plsom neural networks: Applications in medicine and applied sciences
AA Hameed - Journal of Radiation Research and Applied Sciences, 2023 - Elsevier
In recent years, the field of unsupervised learning in neural networks has witnessed
significant advancements. This innovative learning technique holds great promise for …
significant advancements. This innovative learning technique holds great promise for …
An adaptive growing grid model for a non-stationary environment
The self-organizing map (SOM) represents high-dimensional input samples by a 2-
dimensional output topological structure, whereby similar input samples are mapped onto …
dimensional output topological structure, whereby similar input samples are mapped onto …
A simplified climate change model and extreme weather model based on a machine learning method
The emergence of climate change (CC) is affecting and changing the development of the
natural environment, biological species, and human society. In order to better understand …
natural environment, biological species, and human society. In order to better understand …
Feature bagging and extreme learning machines: machine learning with severe memory constraints
With the onset of easy access to supercomputers with high amounts of memory available,
machine learning algorithms have continued to increase the resources necessary to perform …
machine learning algorithms have continued to increase the resources necessary to perform …
基于SOM 聚类和自适应算子选择的高维多目标进化算法
钟沛龙， 黎明， 何超， 陈昊 - 电子学报, 2022 - ejournal.org.cn
在高维多目标进化算法中, 通常利用重组算子产生优质子代来引导种群搜索, 已有研究表明,
利用相似个体进行重组可以提高子代个体质量. 由于自组织映射(Self-Organizing Mapping …
利用相似个体进行重组可以提高子代个体质量. 由于自组织映射(Self-Organizing Mapping …
基于SOM 和关联规则的民机运行风险
熊明兰， 王华伟， 倪晓梅， 蔺瑞管 - 北京航空航天大学学报, 2021 - bhxb.buaa.edu.cn
为充分认知民机风险, 实现从事故中学习, 以重大民机事故(MCAA) 为研究对象挖掘出事故深
层次的致因特征. 针对MCAA 信息具有可读性差, 系统行为具有非线性导致的无法直接获取运行 …
层次的致因特征. 针对MCAA 信息具有可读性差, 系统行为具有非线性导致的无法直接获取运行 …
Evolution of SOMs' Structure and Learning Algorithm: From Visualization of High-Dimensional Data to Clustering of Complex Data
MB Gorzałczany, F Rudziński - Algorithms, 2020 - mdpi.com
In this paper, we briefly present several modifications and generalizations of the concept of
self-organizing neural networks—usually referred to as self-organizing maps (SOMs)—to …
self-organizing neural networks—usually referred to as self-organizing maps (SOMs)—to …
[HTML][HTML] Using machine learning to identify top predictors for nurses' willingness to report medication errors
This paper presents a novel methodology to analyze nurses' willingness to report
medication errors. Parallel Extreme Learning Machines were applied to identify the top …
medication errors. Parallel Extreme Learning Machines were applied to identify the top …