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article

Wykorzystanie techniki AdaBoost w modelach opartych na regresji z wykorzystaniem sztucznej inteligencji

Jacek Wołoszyn

Dydaktyka informatyki > 2019 > 14 > 162-169

Artykuł opisuje wykorzystanie sztucznej inteligencji w obliczeniach regresyjnych. Modele zbudowane w sposób tradycyjny oparte na klasycznych założeniach dostarczają możliwie precy-zyjnych informacji. Sam proces budowy modelu opiera się na wstępnym wyborze zmiennych wykorzystanych do jego tworzenia. Umiejętna selekcja zmiennych ma istotny wpływ na uzyskane parametry. Wykorzystując rozwiązanie przedstawione...

article

Entropy-based regularization of AdaBoost

M. Bereta

Computer Assisted Methods in Engineering and Science > 2017 > Vol. 24, no. 2 > 89--100

In this study, we introduce an entropy-based method to regularize the AdaBoost algorithm. The AdaBoost algorithm is a well-known algorithm used to create aggregated classifiers. In many real-world classification problems in addition to paying special attention classification accuracy of the final classifier, great focus is placed on tuning the number of the so-called weak learners, which are aggregated...

article

Automatic sleep scoring using statistical features in the EMD domain and ensemble methods

A. R. Hassan, M. I. H. Bhuiyan

Biocybernetics and Biomedical Engineering > 2016 > Vol. 36, no. 1 > 248--255

An automatic sleep scoring method based on single channel electroencephalogram (EEG) is essential not only for alleviating the burden of the clinicians of analyzing a high volume of data but also for making a low-power wearable sleep monitoring system feasible. However, most of the existing works are either multichannel or multiple physiological signal based or yield poor algorithmic performance....

article

An FPGA based human detection system with embedded platform

Pei-Yung Hsiao, Shih-Yu Lin, Shih-Shinh Huang, P.Y. Hsiao, more

Microelectronic Engineering > 2015 > 138 > Complete > 42-46

Focusing on the computing speed of the practical machine learning based human detection system at the testing (detecting) stage to reach the real-time requirement in an embedded platform, the idea of iterative computing HOG with FPGA circuit design is proposed. The completed HOG accelerator contains gradient calculation circuit module and histogram accumulation circuit module. The linear SVM classification...

article

Wpływ metody selekcji słów kluczowych na skuteczność klasyfikacji stron internetowych z wykorzystaniem algorytmu boostingu

T. Gąciarz, K. Czajkowski

Czasopismo Techniczne. Nauki Podstawowe > 2012 > R. 109, z. 1-NP > 61--73

Artykuł porusza zagadnienia dotyczące klasyfikacji stron internetowych. Klasyfikacja przeprowadzana jest w oparciu o analizę struktury oraz zawartości stron. Pod uwagę brane są cechy zróżnicowanym charakterze, w tym między innymi cechy strukturalne, wizualne, tekstowe, łączy internetowych. Przy budowie klasyfikatorów wykorzystano algorytm AdaBoost. Skupiono się na wpływie metody selekcji słów kluczowych...

article

Quantitative analysis of reducing sugars in solid‐state fermentation based on NIR combined with GA‐AdaBoost

Meng Zhao, An Sun, Siying He, Luoshui Yu, more

International Journal of Food Science & Technology > 59 > 4 > 2262 - 2274

This study focuses primarily on the real‐time monitoring of reducing sugar levels throughout solid‐state ethanol fermentation. A predictive model for accurate quantification of reducing sugar levels will be formulated through a comprehensive analysis of near‐infrared spectra across different fermentation stages. Building a predictive model using Adaptive Boosting (AdaBoost), The spectral data was...

article

A Machine Learning‐Assisted Approach to a Rapid and Reliable Screening for Mechanically Stable Perovskite‐Based Materials

Russlan Jaafreh, Abhishek Sharan, Muhammad Sajjad, Nirpendra Singh, more

Advanced Functional Materials > 33 > 1 > n/a - n/a

The present work is designed to discover new perovskite‐based materials, which are expected to show high mechanical stability during their applications, using machine learning (ML) techniques, and based on the Pugh's criterion for distinguishing brittle and ductile behaviors. For this purpose, ML models to predict the moduli of materials, bulk (B) and shear (G), are built using their crystal structure...

article

Integrating Vegetation Indices and Spectral Features for Vegetation Mapping from Multispectral Satellite Imagery Using AdaBoost and Random Forest Machine Learning Classifiers

Rashmi Saini

Geomatics and Environmental Engineering > 2023 > Vol. 17, no. 1 > 57--74

Vegetation mapping is an active research area in the domain of remote sensing. This study proposes a methodology for the mapping of vegetation by integrating several vegetation indices along with original spectral bands. The Land Use Land Cover classification was performed by two powerful Machine Learning techniques, namely Random Forest and AdaBoost. The Random Forest algorithm works on the concept...

article

A novel state of charge estimation method of lithium‐ion batteries based on the IWOA‐AdaBoost‐Elman algorithm

Huan Li, Shunli Wang, Monirul Islam, Etse Dablu Bobobee, more

International Journal of Energy Research > 46 > 4 > 5134 - 5151

Lithium‐ion (Li‐ion) battery is a very complex nonlinear system. The data‐driven state of charge (SOC) estimation method of Li‐ion battery avoids complex equivalent circuit modeling and parameter identification, which can describe the nonlinearity of the battery more directly and accurately. To address the problems of low generalization ability, local miniaturization, low prediction accuracy, and...

article

Sentiment analysis of social media data based on chaotic coyote optimization algorithm based time weight‐AdaBoost support vector machine approach

Dharmendra Dangi, Amit Bhagat, Dheeraj Kumar Dixit

Concurrency and Computation: Practice and Experience > 34 > 3 > n/a - n/a

Sentiment analysis or opinion mining is exploited in business, customer services, and so forth, where people provide their opinions in the form of reviews. However, the people's opinions are in a perplexing form such as, sarcasm, irony, and implied meaning which can cause an impact on sentiment analysis. The only way to analyze these words is through context. Nevertheless, there still exist some issues,...

article

Spectral spatial joint feature based convolution neural network for hyperspectral image classification

Diganta Kumar Pathak, Sanjib Kumar Kalita, Dhruba Kumar Bhattacharya

Concurrency and Computation: Practice and Experience > 34 > 3 > n/a - n/a

Hyperspectral sensor generates huge datasets which conveys abundance of information. However, it poses many challenges in the analysis and interpretation of these data. Deep networks like VGG16, VGG19 are difficult to directly apply for hyperspectral image (HSI) classification because of its higher number of layers which in turn requires high level of system resources. This article suggests a novel...

article

Energy Theft Identification using Adaboost Ensembler in the Smart Grids

Muhammad Irfan, Nasir Ayub, Faisal Althobiani, Zain Ali, more

2141-2158

One of the major concerns for the utilities in the Smart Grid (SG) is electricity theft. With the implementation of smart meters, the frequency of energy usage and data collection from smart homes has increased, which makes it possible for advanced data analysis that was not previously possible. For this purpose, we have taken historical data of energy thieves and normal users. To avoid imbalance...

article

Using machine learning to predict fire‐ignition occurrences from lightning forecasts

Ruth Coughlan, Francesca Di Giuseppe, Claudia Vitolo, Christopher Barnard, more

Meteorological Applications > 28 > 1 > n/a - n/a

Lightning‐caused wildfires are a significant contributor to burned areas, with lightning ignitions remaining one of the most unpredictable aspects of the fire environment. There is a clear connection between fuel moisture and the probability of ignition; however, the mechanisms are poorly understood and predictive methods are underdeveloped. Establishing a lightning–ignition relationship would be...

article

Adaptive Boosting (AdaBoost)‐based multiwavelength spatial frequency domain imaging and characterization for ex vivo human colorectal tissue assessment

Shuying Li, Yifeng Zeng, William C. Chapman, Mohsen Erfanzadeh, more

Journal of Biophotonics > 13 > 6 > n/a - n/a

The current gold standard diagnostic test for colorectal cancer remains histological inspections of endoluminal neoplasia in biopsy specimens. However, biopsy site selection requires visual inspection of the bowel, typically with a white‐light endoscope. Therefore, this technique is poorly suited to detect small or innocuous‐appearing lesions. We hypothesize that an alternative modality—multiwavelength...

article

Modeling Equilibrium Systems of Amine‐Based CO₂ Capture by Implementing Machine Learning Approaches

Mohammad M. Ghiasi, Saeid Abedi‐Farizhendi, Amir H. Mohammadi

Environmental Progress & Sustainable Energy > 38 > 5 > n/a - n/a

Precise calculation of carbon dioxide equilibrium solubility in aqueous amine solutions is decisive in the success of establishment or maintenance of amine‐based absorptive carbon dioxide capture processes. To implement the AdaBoost algorithm in conjunction with the classification and regression tree (AdaBoost‐CART) aimed at developing models to accurately estimate the equilibrium absorption of carbon...

article

Vehicle detection based on visual attention mechanism and adaboost cascade classifier in intelligent transportation systems

Xu Chen, Lei Liu, Yubin Deng, Xiangyu Kong

Optical and Quantum Electronics > 2019 > 51 > 8 > 1-18

Robust and efficient vehicle detection is an essential task in intelligent transportation systems (ITS). Unfortunately, due to a great diversity of vehicle profiles and outdoor illumination conditions, it is a challenge to detect vehicles effectively. This paper proposes a method for high-performance vehicle detection based on visual attention mechanism and AdaBoost cascade classifier. Our method...

article

Adaboost-based security level classification of mobile intelligent terminals

Feng Wang, Dingde Jiang, Hong Wen, Houbing Song

The Journal of Supercomputing > 2019 > 75 > 11 > 7460-7478

With the rapid development of Internet of Things, massive mobile intelligent terminals are ready to access edge servers for real-time data calculation and interaction. However, the risk of private data leakage follows simultaneously. As the administrator of all intelligent terminals in a region, the edge server needs to clarify the ability of the managed intelligent terminals to defend against malicious...

article

Feature Extraction Using Conformal Geometric Algebra for AdaBoost Algorithm Based In-plane Rotated Face Detection

Tuan M. Pham, Danh C. Doan, Eckhard Hitzer

Advances in Applied Clifford Algebras > 2019 > 29 > 4 > 1-19

In this paper, we propose a novel face detection method based on the AdaBoost algorithm. In the past few years, a variety of variant AdaBoost approaches has been proposed and obtained increasing success in both performance and robustness. However, those approaches have not focused much on the geometric characteristics of face images. A new way to apply AdaBoost is introduced in this paper with the...

article

A Machine Learning Based Approach for Automatic Rebar Detection and Quantification of Deterioration in Concrete Bridge Deck Ground Penetrating Radar B-scan Images

Pouria Asadi, Mayrai Gindy, Marco Alvarez

KSCE Journal of Civil Engineering > 2019 > 23 > 6 > 2618-2627

Ground penetrating radar (GPR) is a non-destructive method (NDT) for subsurface object identification. Interpretation of GPR data is often done manually by an engineer, which is a time-intensive task and requires moderate to significant level of training. The authors proposed a novel machine learning based processing for automatic interpretation and quantification of concrete bridge deck GPR B-scan...

article

Aerolysin Nanopore Identification of Single Nucleotides Using the AdaBoost Model

Xue-Jie Sui, Meng-Yin Li, Yi-Lun Ying, Bing-Yong Yan, more

Journal of Analysis and Testing > 2019 > 3 > 2 > 134-139

Nanopores employ the ionic current from the single molecule blockage to identify the structure, conformation, chemical groups and charges of a single molecule. Despite the tremendous development in designing sensitive pore-forming materials, at some extent, the analyte with the single group difference still exhibits similar residual current or duration time. The serious overlap in the statistical...

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Search results

Wykorzystanie techniki AdaBoost w modelach opartych na regresji z wykorzystaniem sztucznej inteligencji

Entropy-based regularization of AdaBoost

Automatic sleep scoring using statistical features in the EMD domain and ensemble methods

An FPGA based human detection system with embedded platform

Wpływ metody selekcji słów kluczowych na skuteczność klasyfikacji stron internetowych z wykorzystaniem algorytmu boostingu

Quantitative analysis of reducing sugars in solid‐state fermentation based on NIR combined with GA‐AdaBoost

A Machine Learning‐Assisted Approach to a Rapid and Reliable Screening for Mechanically Stable Perovskite‐Based Materials

Integrating Vegetation Indices and Spectral Features for Vegetation Mapping from Multispectral Satellite Imagery Using AdaBoost and Random Forest Machine Learning Classifiers

A novel state of charge estimation method of lithium‐ion batteries based on the IWOA‐AdaBoost‐Elman algorithm

Sentiment analysis of social media data based on chaotic coyote optimization algorithm based time weight‐AdaBoost support vector machine approach

Spectral spatial joint feature based convolution neural network for hyperspectral image classification

Energy Theft Identification using Adaboost Ensembler in the Smart Grids

Using machine learning to predict fire‐ignition occurrences from lightning forecasts

Adaptive Boosting (AdaBoost)‐based multiwavelength spatial frequency domain imaging and characterization for ex vivo human colorectal tissue assessment

Modeling Equilibrium Systems of Amine‐Based CO₂ Capture by Implementing Machine Learning Approaches

Vehicle detection based on visual attention mechanism and adaboost cascade classifier in intelligent transportation systems

Adaboost-based security level classification of mobile intelligent terminals

Feature Extraction Using Conformal Geometric Algebra for AdaBoost Algorithm Based In-plane Rotated Face Detection

A Machine Learning Based Approach for Automatic Rebar Detection and Quantification of Deterioration in Concrete Bridge Deck Ground Penetrating Radar B-scan Images

Aerolysin Nanopore Identification of Single Nucleotides Using the AdaBoost Model

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