作者: 自愛 時間: 2025-3-21 22:05 作者: 損壞 時間: 2025-3-22 01:53
Sweden, France, USA and the EECduring the past two decades. Then, we propose to address these key challenges in E-nose, which are sensor induced and sensor specific. This chapter is closed by a statement of the objective of the research, a brief summary of the work, and a general outline of the overall structure of this book.作者: Archipelago 時間: 2025-3-22 06:41 作者: 束縛 時間: 2025-3-22 10:57 作者: 支形吊燈 時間: 2025-3-22 16:38 作者: 支形吊燈 時間: 2025-3-22 20:52
Sweden, France, USA and the EECduring the past two decades. Then, we propose to address these key challenges in E-nose, which are sensor induced and sensor specific. This chapter is closed by a statement of the objective of the research, a brief summary of the work, and a general outline of the overall structure of this book.作者: 刺穿 時間: 2025-3-22 23:20
Secondary Nucleation — A Revieworithms, signal de-noising algorithms, pattern recognition algorithms, and drift compensation algorithms that have been fully studied in electronic noses. Then, the challenges of E-nose technology are defined and described, including drift compensation, disturbance elimination, and discreteness corr作者: Hamper 時間: 2025-3-23 02:40
Work Autonomy and Product Innovation, using a multi-sensor system. The estimation accuracy in actual application is concerned too much by manufacturers and researchers. This chapter analyzes the application of different bio-inspired and heuristic techniques to improve the concentration estimation in experimental electronic nose applica作者: 是貪求 時間: 2025-3-23 06:33
Alexander Romanovsky,Martyn Thomass of indoor contaminants using chaos-based optimization artificial neural network integrated into our E-nose instrument. Back-propagation neural network (BPNN) has been the common pattern recognition algorithm for E-nose; however, it has local optimal flaw. This chapter presents a novel chaotic sequ作者: monogamy 時間: 2025-3-23 12:13 作者: 魅力 時間: 2025-3-23 15:44 作者: CALL 時間: 2025-3-23 19:53 作者: 有毒 時間: 2025-3-24 01:03 作者: 出生 時間: 2025-3-24 06:18 作者: Biguanides 時間: 2025-3-24 07:58 作者: Fester 時間: 2025-3-24 14:29 作者: ODIUM 時間: 2025-3-24 16:07 作者: 角斗士 時間: 2025-3-24 21:59
Paul R. Ferguson,Glenys J. Fergusonrift and interference problem of E-nose. The framework consists of two parts: (1) domain correction (DC) that makes the distributions of two domains close; (2) adaptive extreme learning machine (AELM) that learns a transferable classifier at decision level. This method is motivated by the idea of tr作者: 歌劇等 時間: 2025-3-24 23:11
Invention, Innovation and Diffusion, for each sensor may be extracted; second, consider that the manual labeling of artificial olfaction data in real-time detection is difficult and hardly impossible, semi-supervised learning strategy is expected to be a breakthrough and overcome the problem of insufficient labeled data in artificial 作者: 去才蔑視 時間: 2025-3-25 05:00
Other inorganic electrolytic processes,pecificity and stability of electronic nose in practical application. This chapter presents an on-line counteraction of unwanted odor interference based on pattern recognition for the first time. Six kinds of target gases and four kinds of unwanted odor interferences were experimentally studied. Fir作者: 警告 時間: 2025-3-25 08:15
https://doi.org/10.1007/978-981-13-2167-2Electronic Nose; Pattern Recognition; Drift Compensation; Odor Recognition; Machine Learning; Gas Sensing作者: Constitution 時間: 2025-3-25 14:09
978-981-13-4741-2Springer Nature Singapore Pte Ltd. 2018作者: COST 時間: 2025-3-25 16:17 作者: COLON 時間: 2025-3-25 20:38
Industrial Development and Eco-Tourismsent analysis (PCA), an effective kernel PCA plus NDA method (KNDA) is proposed for rapid detection of gas mixture components. In this chapter, the NDA framework is derived with specific implementations. Experimental results demonstrate the superiority of the proposed KNDA method in multi-class recognition.作者: 金桌活畫面 時間: 2025-3-26 01:11 作者: 大包裹 時間: 2025-3-26 08:21 作者: Arthr- 時間: 2025-3-26 11:30
Cross-Domain Subspace Learning Approachk called cross-domain extreme learning machine (CdELM), which aims at learning a common (shared) subspace across domains. Experiments on drifted E-nose datasets demonstrate that the proposed CdELM method significantly outperforms other compared methods.作者: 痛得哭了 時間: 2025-3-26 13:01
Chaos-Based Neural Network Optimization Approachence optimization BPNN method. Experimental results demonstrate the superiority and efficiency of the portable E-nose instrument integrated into chaos-based artificial neural network optimization algorithms in real-time monitoring of air quality in dwellings.作者: Calculus 時間: 2025-3-26 19:50
Discriminative Support Vector Machine-Based Odor Classificationntal results demonstrate that the HSVM model outperforms other classifiers in general. Also, HSVM classifier preliminarily shows its superiority in solution to discrimination in various electronic nose applications.作者: Indicative 時間: 2025-3-26 23:09 作者: 簡略 時間: 2025-3-27 02:15
Domain Correction-Based Adaptive Extreme Learning Machineansfer learning, especially from the perspective of domain correction and decision making, to realize the knowledge transfer for interference suppression and drift compensation. Experiments on a background interference dataset and a public benchmark sensor drift dataset via E-nose verify the effectiveness of the proposed DC-AELM method.作者: Immunization 時間: 2025-3-27 05:46 作者: 貪心 時間: 2025-3-27 10:17
The Geography of Design in the Cityntal results demonstrate that the HSVM model outperforms other classifiers in general. Also, HSVM classifier preliminarily shows its superiority in solution to discrimination in various electronic nose applications.作者: 伸展 時間: 2025-3-27 13:55
Costs of Energy and Drying Equipment,n; second, in the process of establishing classifiers ensemble, a new fusion approach conducting an effective base classifier weighted method is proposed. Experimental results show that the average classification accuracy of the proposed method has been significantly improved over base classifiers and majority voting-based fusion strategy.作者: 個阿姨勾引你 時間: 2025-3-27 18:49
Paul R. Ferguson,Glenys J. Fergusonansfer learning, especially from the perspective of domain correction and decision making, to realize the knowledge transfer for interference suppression and drift compensation. Experiments on a background interference dataset and a public benchmark sensor drift dataset via E-nose verify the effectiveness of the proposed DC-AELM method.作者: ALT 時間: 2025-3-28 01:35
Book 2018aling to readers from the fields of artificial intelligence, computer science, electrical engineering, electronics, and instrumentation science, it addresses three main areas: First, readers will learn how to apply machine learning, pattern recognition and signal processing algorithms to real percep作者: 按時間順序 時間: 2025-3-28 04:12
Work Autonomy and Product Innovation,work. We present the performance of a particle swarm optimization technique, an adaptive genetic strategy, and a back-propagation artificial neural network approach to perform concentration estimation of chemical gases and improve the intelligence of an E-nose.作者: 彩色的蠟筆 時間: 2025-3-28 09:54
Pfadwechsel — schwierig aber notwendigmonstrates the obvious chaotic behavior through the Lyapunov exponents. Results demonstrate that the proposed model can make long-term and accurate prediction of time series chemical sensor baseline and drift.作者: 過份艷麗 時間: 2025-3-28 14:03 作者: 治愈 時間: 2025-3-28 18:30 作者: antidepressant 時間: 2025-3-28 21:17
Other inorganic electrolytic processes, constructed for correction. Finally, an effective signal correction method was employed for E-nose data. Experimental results in the real case-studies demonstrate the effectiveness of the presented model in E-nose based on MOS gas sensors array.作者: Cupidity 時間: 2025-3-28 23:40 作者: Plaque 時間: 2025-3-29 07:04 作者: 得意牛 時間: 2025-3-29 08:44
Domain Adaptation Guided Drift Compensationin classifier with drift compensation. Experiments on the popular sensor drift data of multiple batches clearly demonstrate that the proposed DAELM significantly outperforms existing drift compensation methods.作者: 祝賀 時間: 2025-3-29 11:38
Domain Regularized Subspace Projection Method and anti-drift is manifested with a well-solved projection matrix in real application. Experiments on synthetic data and real datasets demonstrate the effectiveness and efficiency of the proposed anti-drift method in comparison to state-of-the-art methods.作者: Yag-Capsulotomy 時間: 2025-3-29 16:00
Pattern Recognition-Based Interference Reduction constructed for correction. Finally, an effective signal correction method was employed for E-nose data. Experimental results in the real case-studies demonstrate the effectiveness of the presented model in E-nose based on MOS gas sensors array.作者: Nonconformist 時間: 2025-3-29 22:58
Introductionduring the past two decades. Then, we propose to address these key challenges in E-nose, which are sensor induced and sensor specific. This chapter is closed by a statement of the objective of the research, a brief summary of the work, and a general outline of the overall structure of this book.作者: Permanent 時間: 2025-3-30 03:10 作者: 有權(quán)威 時間: 2025-3-30 04:33
Heuristic and Bio-inspired Neural Network Model using a multi-sensor system. The estimation accuracy in actual application is concerned too much by manufacturers and researchers. This chapter analyzes the application of different bio-inspired and heuristic techniques to improve the concentration estimation in experimental electronic nose applica作者: dermatomyositis 時間: 2025-3-30 08:32 作者: restrain 時間: 2025-3-30 12:48
Multilayer Perceptron-Based Concentration Estimationsed to analytes with different concentrations. Therefore, the characteristics of cross sensitivities and broad spectrum of non-selective chemical sensors stimulate the fast development of portable and low-cost electronic nose. Simultaneous concentration estimation of multiple kinds of chemicals is a作者: adroit 時間: 2025-3-30 17:34
Discriminative Support Vector Machine-Based Odor Classification HSVM model has been rigorously evaluated. In addition, we have also compared with existing methods including Euclidean distance to centroids (EDC), simplified fuzzy ARTMAP network (SFAM), multilayer perceptron neural network (MLP) based on back-propagation, individual FLDA, and single SVM. Experime作者: Cupidity 時間: 2025-3-30 22:58
Local Kernel Discriminant Analysis-Based Odor Recognitionn-class Laplacian scatter matrices are designed from sample to sample, respectively, to characterize the between-class separability and the within-class compactness. Then, a discriminant projection matrix is solved by simultaneously maximizing the between-class Laplacian scatter and minimizing the w作者: 使顯得不重要 時間: 2025-3-31 02:46
