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检索条件"主题词=firefly algorithm"
1747 条 记 录,以下是171-180 订阅
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Multi-step ahead electricity price forecasting using a hybrid model based on two-layer decomposition technique and BP neural network optimized by firefly algorithm
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APPLIED ENERGY 2017年 190卷 390-407页
作者: Wang, Deyun Luo, Hongyuan Grunder, Olivier Lin, Yanbing Guo, Haixiang China Univ Geosci Sch Econ & Management Wuhan 430074 Peoples R China China Univ Geosci Mineral Resource Strategy & Policy Res Ctr Wuhan 430074 Peoples R China Univ Bourgogne Franche Comte UTBM IRTES Rue Thierry Mieg F-90010 Belfort France
In the deregulated competitive electricity market, the price which reflects the relationship between electricity supply and demand is one of the most important elements, making it crticial for all market participants ... 详细信息
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Multi-level Segmentation of Fruits Using Modified firefly algorithm (Apr, 10.1007/s12161-022-02290-7, 2022)
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FOOD ANALYTICAL METHODS 2022年 第11期15卷 2901-2901页
作者: Chaturvedi, Rekha Sharma, Abhay Bhargava, Anuja Rajpurohit, Jitendra Gothwal, Pushpa Manipal Univ Jaipur Jaipur Rajasthan India GLA Univ Mathura India Univ Petr & Energy Studies Dehra Dun Uttarakhand India
The data explosion caused by the Internet and its applications has given researchers immense scope for data analysis. A large amount of data is available in form of images. Image processing is required for better unde... 详细信息
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Tuning parameter estimation in SCAD-support vector machine using firefly algorithm with application in gene selection and cancer classification
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COMPUTERS IN BIOLOGY AND MEDICINE 2018年 103卷 262-268页
作者: Al-Thanoon, Niam Abdulmunim Qasim, Omar Saber Algamal, Zakariya Yahya Univ Mosul Dept Operat Res & Artificial Intelligence Mosul Iraq Univ Mosul Dept Math Mosul Iraq Univ Mosul Dept Stat & Informat Mosul Iraq
In cancer classification, gene selection is one of the most important bioinformatics related topics. The selection of genes can be considered to be a variable selection problem, which aims to find a small subset of ge... 详细信息
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IFACNN: efficient DDoS attack detection based on improved firefly algorithm to optimize convolutional neural networks
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MATHEMATICAL BIOSCIENCES AND ENGINEERING 2022年 第2期19卷 1280-1303页
作者: Wang, Jiushuang Liu, Ying Feng, Huifen Beijing Jiaotong Univ Natl Engn Lab Interconnect Technol Next Generat I Beijing Peoples R China
Network security has become considerably essential because of the expansion of internet of things (IoT) devices. One of the greatest hazards of today's networks is distributed denial of service (DDoS) attacks, whi... 详细信息
来源: 评论
Shape and Size Optimization of Truss Structures under Frequency Constraints Based on Hybrid Sine Cosine firefly algorithm
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Computer Modeling in Engineering & Sciences 2023年 第1期134卷 405-428页
作者: Ran Tao Xiaomeng Yang Huanlin Zhou Zeng Meng School of Civil Engineering Hefei University of TechnologyHefei230009China
Shape and size optimization with frequency constraints is a highly nonlinear problem withmixed design variables,non-convex search space,and multiple local ***,a hybrid sine cosine firefly algorithm(HSCFA)is proposed t... 详细信息
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A novel efficient substitution-box design based on firefly algorithm and discrete chaotic map
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NEURAL COMPUTING & APPLICATIONS 2019年 第11期31卷 7201-7210页
作者: Ahmed, Hussam A. Zolkipli, Mohamad Fadli Ahmad, Musheer Univ Malaysia Pahang Fac Comp Syst & Software Engn Lebuhraya Tun Razak Kuantan 26300 Pahang Darul Ma Malaysia Jamia Millia Islamia Dept Comp Engn New Delhi 110025 India
Substitution boxes are essential nonlinear components responsible to impart strong confusion and security in most of modern symmetric ciphers. Constructing efficient S-boxes has been a prominent topic of interest for ... 详细信息
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Support vector regression with modified firefly algorithm for stock price forecasting
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APPLIED INTELLIGENCE 2019年 第5期49卷 1658-1674页
作者: Zhang, Jun Teng, Yu-Fan Chen, Wei Capital Univ Econ & Business Sch Informat Beijing Peoples R China
The support vector regression (SVR) has been employed to deal with stock price forecasting problems. However, the selection of appropriate kernel parameters is crucial to obtaining satisfactory forecasting performance... 详细信息
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An optimistic firefly algorithm-based deep learning approach for sentiment analysis of COVID-19 tweets
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MATHEMATICAL BIOSCIENCES AND ENGINEERING 2023年 第2期20卷 2382-2407页
作者: Swapnarekha, H. Nayak, Janmenjoy Behera, H. S. Dash, Pandit Byomakesha Pelusi, Danilo Aditya Inst Technol & Management AITAM Dept Informat Technol Tekkali 532201 Andhra Pradesh India Maharaja Sriram Chandra Bhanja Deo Univ Dept Comp Sci Baripada 757003 Odisha India Veer Surendra Sai Univ Technol Dept Informat Technol Burla 768018 India Univ Teramo Commun Sci Coste St Agostino Campus I-64100 Teramo Italy
The unprecedented rise in the number of COVID-19 cases has drawn global attention, as it has caused an adverse impact on the lives of people all over the world. As of December 31, 2021, more than 2,86,901,222 people h... 详细信息
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A new fuzzy membership assignment and model selection approach based on dynamic class centers for fuzzy SVM family using the firefly algorithm
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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2016年 第3期24卷 1797-U5073页
作者: Almasi, Omid Naghash Rouhani, Modjtaba Islamic Azad Univ Mashhad Branch Young Researchers & Elite Club Mashhad Iran Ferdowsi Univ Mashhad Fac Engn Dept Comp Engn Mashhad Iran
The support vector machine (SVM) is a powerful tool for classification problems. Unfortunately, the training phase of the SVM is highly sensitive to noises in the training set. Noises are inevitable in real-world appl... 详细信息
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Discrete Optimum Design of Truss Structures by an Improved firefly algorithm
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ADVANCES IN STRUCTURAL ENGINEERING 2014年 第10期17卷 1517-1530页
作者: Baghlani, A. Makiabadi, M. H. Sarcheshmehpour, M. Shiraz Univ Technol Fac Civil & Environm Engn Shiraz Iran Sharif Univ Technol Fac Civil Engn Tehran Iran
This paper presents an improved firefly algorithm (FA) for fast optimization of truss structures with discrete variables. The enhanced accelerated firefly algorithm (AFA) is a simple, but very effective modification o... 详细信息
来源: 评论