SEVERAL SPECIAL FUNCTIONS IN FRACTALS AND APPLICATIONS OF THE FRACTAL IN MACHINE LEARNING

被引：0

作者：

Wang, Jun ^{[1
,2
]}

Cao, Lei ^{[1
,2
]}

Chen, Xiliang ^{[1
,2
]}

Tang, Wei ^{[1
,2
]}

Xu, Zhixiong ^{[3
]}

机构：

[1] Army Engn Univ PLA, Nanjing 211101, Peoples R China

[2] Troops 78092, Chengdu 610031, Peoples R China

[3] Army Acad Border & Coastal Def, Xian 710100, Peoples R China

来源：

FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY | 2022年 / 30卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Unbounded Variation; Continuous Function; Machine Learning; Fractals; FRACTIONAL CALCULUS; DIMENSIONS;

D O I：

10.1142/S0218348X22500311

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

The focus of this paper is to study unbounded variation functions from the perspective of Holder conditions. Three special unbounded variation functions have been constructed. The first is a continuous function of unbounded variation that satisfies the Holder condition of a given order and the second is a continuous function of unbounded variation that does not satisfy the Holder condition of any order. The third is a continuous function of unbounded variation defined on any sub-interval of the interval I. Then, specific fractal dimension analysis of the above functions and relevant conclusions have been investigated. Finally, combining functional analysis and reinforcement learning, the convergence of reinforcement learning algorithms can be proved in unified framework.

引用

页数：9

共 50 条

[21] Applications of machine learning in healthcare [J].

Aracena, Claudio ;

Villena, Fabian ;

Arias, Felipe ;

Dunstan, Jocelyn .

REVISTA MEDICA CLINICA LAS CONDES, 2022, 33 (06) :568-575

[22] An Analysis of Several Machine Learning Algorithms for Imbalanced Classes [J].

Datta, Soma ;

Arputharaj, Anuprabha .

2018 5TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING & MACHINE INTELLIGENCE (ISCMI), 2018, :22-27

[23] From the Editors of the Special Issue on Current Applications and Innovations of Artificial Intelligence and Machine Learning in Aerospace [J].

Mohammed, Sabah ;

Chang, Ruay-Shiung ;

Ramos, Carlos ;

Kim, Tai-Hoon .

IEEE AEROSPACE AND ELECTRONIC SYSTEMS MAGAZINE, 2022, 37 (06) :4-5

[24] Machine learning and deep learning: Introduction and applications [J].

Nakashima T. .

Zairyo, 2020, 9 (633-639) :633-639

[25] A Review of Machine Learning and Deep Learning Applications [J].

Shinde, Pramila P. ;

Shah, Seema .

2018 FOURTH INTERNATIONAL CONFERENCE ON COMPUTING COMMUNICATION CONTROL AND AUTOMATION (ICCUBEA), 2018,

[26] Several models for tunnel boring machine performance prediction based on machine learning [J].

Mahmoodzadeh, Arsalan ;

Nejati, Hamid Reza ;

Ibrahim, Hawkar Hashim ;

Ali, Hunar Farid Hama ;

Mohammed, Adil Hussein ;

Rashidi, Shima ;

Majeed, Mohammed Kamal .

GEOMECHANICS AND ENGINEERING, 2022, 30 (01) :75-91

[27] Fractional calculus and its applications involving functions of several variables [J].

Kalia, RN ;

Srivastava, HM .

APPLIED MATHEMATICS LETTERS, 1999, 12 (05) :19-23

[28] Integrating eye gaze into machine learning using fractal curves [J].

Newport, Robert Ahadizad ;

Liu, Sidong ;

Di Ieva, Antonio .

GAZE MEETS MACHINE LEARNING WORKSHOP, VOL 210, 2022, 210 :113-126

[29] Introduction to the Special Issue on Machine Learning Methods and Applications in Large-Scale Route Planning Problems [J].

Winkenbach, Matthias ;

Spinler, Stefan ;

Pachon, Julian ;

Konduri, Karthik .

TRANSPORTATION SCIENCE, 2024, 58 (01) :1-7

[30] Machine learning applications in nuclear physics [J].

He WanBing ;

He JunJie ;

Wang Rui ;

Ma YuGang .

SCIENTIA SINICA-PHYSICA MECHANICA & ASTRONOMICA, 2022, 52 (05)

← 1 2 3 4 5 →