Zobrazeno 1 - 10
of 91
pro vyhledávání: '"Khamron Sunat"'
Publikováno v:
IEEE Access, Vol 12, Pp 35868-35898 (2024)
This paper presents the Bias-Boosted Extreme Learning Machine guided Brain Emotional Learning (B2ELM-BEL) model, a significant advancement in chaotic time series prediction that effectively incorporates knowledge transfer learning. Integrating tradit
Externí odkaz:
https://doaj.org/article/abbad86f99564fe8a50812a9511e035b
Publikováno v:
IEEE Access, Vol 10, Pp 128800-128823 (2022)
This paper presents the logical relationships of Aristotle’s square of opposition on four basic categorial prepositions (i.e., contrary, contradictory, subcontrary, and subaltern) of Joint Opposite Selection (JOS). JOS brings a mutual reinforcement
Externí odkaz:
https://doaj.org/article/0fe7432c9a9145a8b8a188c99f4bcde4
Publikováno v:
Healthcare, Vol 11, Iss 5, p 697 (2023)
The procedure to diagnose anemia is time-consuming and resource-intensive due to the existence of a multitude of symptoms that can be felt physically or seen visually. Anemia also has several forms, which can be distinguished based on several charact
Externí odkaz:
https://doaj.org/article/ada801ce0bf34d8f93f2df5a958096f0
Publikováno v:
Engineering and Applied Science Research, Vol 47, Iss 1, Pp 1-26 (2020)
The fruit fly optimization algorithm (FOA) was a recently proposed. FOA has a number of advantages over other nature-inspired algorithms such as its simple structure and ease of implementation. However, the FOA’s search procedures present a problem
Externí odkaz:
https://doaj.org/article/920f9ade94ab4ad0b216adf32baeef42
Publikováno v:
Engineering and Applied Science Research, Vol 46, Iss 4, Pp 276-284 (2019)
Data splitting is an important step in artificial neural network (ANN) models, which is found in the form of training and testing subsets. In general, a random data splitting method is favored to divide a pool of samples into subsets, without conside
Externí odkaz:
https://doaj.org/article/4119f0c8a3ba4d34bfbfb032057a2148
Publikováno v:
IEEE Access, Vol 7, Pp 20894-20919 (2019)
This paper proposes a novel method that addresses the selection of the dominant patterns of the histograms of oriented gradients (DPHOGs) in vehicle detection. HOG features lead to an expensive classification with high misclassification rates since H
Externí odkaz:
https://doaj.org/article/fbcaeab309eb401eb37f5201abf36daa
Autor:
Pakarat Musikawan, Khamron Sunat, Yanika Kongsorot, Punyaphol Horata, Sirapat Chiewchanwattana
Publikováno v:
IEEE Access, Vol 7, Pp 26909-26932 (2019)
A feedforward neural network ensemble trained through metaheuristic algorithms has been proposed by researchers to produce a group of optimal neural networks. This method, however, has proven to be very time-consuming during the optimization process.
Externí odkaz:
https://doaj.org/article/48861e2b663d491988635ec9643207ab
Publikováno v:
IEEE Access, Vol 7, Pp 83932-83961 (2019)
Several contemporary algorithms, including cuckoo search (CS), were applied to the CEC 2017 problem set, which includes a wide variety of 120 very difficult subproblems. We found that the algorithms were ineffective, especially when the number of dim
Externí odkaz:
https://doaj.org/article/9fbf4890a6874ea0bcf7bf6f5028c32e
Publikováno v:
Symmetry, Vol 12, Iss 11, p 1782 (2020)
This paper presents a method for feature selection in a high-dimensional classification context. The proposed method finds a candidate solution based on quality criteria using subset searching. In this study, the competitive swarm optimization (CSO)
Externí odkaz:
https://doaj.org/article/f76ecc6f00af438aa38598c26b9b2c97
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 43:4987-5000
In the business sector, predicting the movement of the Stock Exchange of Thailand (SET) index is challenging. Due to worldwide stock market fluctuations, investors commonly invest in price-changing businesses solely in the long term. Therefore, an ac