基于混合径向基函数网络和组合优化模型的医疗疾病诊断模型

3区 计算机科学 Q1 Computer Science Journal of Ambient Intelligence and Humanized Computing Pub Date : 2024-08-03 DOI:10.1007/s12652-024-04840-9
Taoufyq Elansari, Mohammed Ouanan, Hamid Bourray
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引用次数: 0

摘要

混合径向基函数神经网络(MRBFNN)是一种人工神经网络,其隐藏层采用径向基函数(RBF)作为激活函数。隐藏层中神经元的数量和这些神经元中使用的 RBF 函数的选择会极大地影响 MRBFNN 学习算法的收敛性,并影响神经网络的整体性能。本文提出了一种非线性优化模型和算法,用于为 MRBFNN 选择合适的架构和学习策略。为了逼近模型的解,我们采用了基于粒子群优化(PSO)技术的算法。我们将在医疗疾病诊断(MDD)中应用我们的方法。所获得的数值结果证明了所提出的理论方法的有效性,并强调了新建模方法的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A classifier based on mixed radial basis function network and combinatorial optimization model for medical diseases diagnosis

The Mixed Radial Basis Function Neural Network (MRBFNN) is an artificial neural network that employs Radial Basis Functions (RBFs) as activation functions in its hidden layer. The number of neurons in the hidden layer and the choice of RBF functions used in these neurons significantly affect the convergence of MRBFNN learning algorithms and impact the overall performance of neural networks. This article presents a nonlinear optimization model and an algorithm to select an appropriate architecture and learning strategy for MRBFNN. To approximate the solution of our model, we utilized an algorithm based on Particle Swarm Optimization (PSO) techniques. We will apply our approach in Medical Diseases Diagnosis (MDD). The numerical results obtained demonstrate the effectiveness of the proposed theoretical approach and underscore the advantages of the new modeling methodology.

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来源期刊
Journal of Ambient Intelligence and Humanized Computing
Journal of Ambient Intelligence and Humanized Computing COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
9.60
自引率
0.00%
发文量
854
期刊介绍: The purpose of JAIHC is to provide a high profile, leading edge forum for academics, industrial professionals, educators and policy makers involved in the field to contribute, to disseminate the most innovative researches and developments of all aspects of ambient intelligence and humanized computing, such as intelligent/smart objects, environments/spaces, and systems. The journal discusses various technical, safety, personal, social, physical, political, artistic and economic issues. The research topics covered by the journal are (but not limited to): Pervasive/Ubiquitous Computing and Applications Cognitive wireless sensor network Embedded Systems and Software Mobile Computing and Wireless Communications Next Generation Multimedia Systems Security, Privacy and Trust Service and Semantic Computing Advanced Networking Architectures Dependable, Reliable and Autonomic Computing Embedded Smart Agents Context awareness, social sensing and inference Multi modal interaction design Ergonomics and product prototyping Intelligent and self-organizing transportation networks & services Healthcare Systems Virtual Humans & Virtual Worlds Wearables sensors and actuators
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