Thermal Imagery Feature Extraction Techniques and the Effects on Machine Learning Models for Smart HVAC Efficiency in Building Energy

Acquaah, Yaa; Gokaraju, Balakrishna; Tesiero, Raymond; Monty, Gregory H.

doi:10.3390/rs13193847

Cited by 12 publications

(2 citation statements)

References 36 publications

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“…Although Fourier analysis could be used to represent certain trends, it is inefficient in capturing abrupt changes. A wavelet is a rapidly decaying wave-like oscillation that has zero mean and exists for a finite duration and in different sizes and shapes [ 38 ]. Continuous and discrete are the two main wavelet transforms.…”

Section: Methodsmentioning

confidence: 99%

Economy and elderly population, complementary or contradictory: A cross-continental wavelet coherence and cross-country Granger causality study

Galappaththi

Jayathilaka²,

Rajamanthri³

et al. 2023

PLoS ONE

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The aim of this study is to explore the causal relationship between the economy and the elderly population globally as well as continent-wise. This research was designed as a continent-wide study to investigate the differences between several regions simultaneously. The economy was measured by the Gross Domestic Product (GDP) per capita growth rate while the population aged above 65 as a percentage of the total was considered the elderly population. A panel dataset published by the World Bank for a period of six decades from 1961 to 2020 covering 84 countries was used as data for the analysis. Wavelet coherence was the methodology used for the study since it was considered suitable to present causality as well as the causal direction between the two variables for different sections during the six decades. Thereafter, Granger causality was applied for a cross-country analysis to gain further insights on the causality of individual countries over the years. Findings of the study reveal that the causality and its direction have been changing over time for most continents. Negative correlations with the leading variable interchanging with time are evident for the majority of the regions. Nevertheless, results indicate that in a global perspective, elderly population predominantly leads the economic growth with a positive correlation. Research approach allows ascertaining the short-term and medium-term changes that occurred concerning the direction of the relationship throughout the stipulated period of the study, which could not be drawn by any previous study. Even though region-wise literature is available on this topic, global studies for decades have not been conducted yet.

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Section: Methodsmentioning

confidence: 99%

Economy and elderly population, complementary or contradictory: A cross-continental wavelet coherence and cross-country Granger causality study

Galappaththi

Jayathilaka²,

Rajamanthri³

et al. 2023

PLoS ONE

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show abstract

“…The breast disease study reported by the World Health Organization (WHO) confirms that breast cancer is the most impacted cancer occurred among women [1]. The study investigates the treatments and arrangements that support to enhancement of the cancer patient's survival rate [2].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Statistical and Texture Features with DenseNet 121 for Breast Cancer Classification

2023

IJIES

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Cancers are aggressive which is coupled with higher mortality rates and remain a major life-threatening factor in humans. Thus, early detection of cancer among patients is important as it showed a great survival chance. Therefore, early detection provides the patients with greater survival chances. The diagnosis performed for the mammography images are quite expensive and also radiations produced during the process were harmful to the patients. Thermography is a cost-effective and invasive method compared to mammography images and thus has reached its popularity. The present research is aimed to create the Machine Learning (ML) models using Convolutional Neural Networks (CNN) approaches which were created based on the machine learning models. The present research work utilized the DMR-IR dataset for the results evaluation and performance evaluation of the model which has been verified with datasets. The feature extraction process utilizes a machine learning algorithm to overcome the problems. The developed models were engaged in sophisticated ways to extract the features to improve the classification of the model. The Hybrid statistical and texture feature extraction technique extracts the features better in turn improved the model training. The results showed that the proposed hybrid feature extraction with the Dense Net 121 model obtained better

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Machine Learning Techniques to Predict Real Time Thermal Comfort, Preference, Acceptability, and Sensation for Automation of HVAC Temperature

Acquaah

Gokaraju

Tesiero

et al. 2022

Advances and Trends in Artificial Intelligence. Theory and Practices in Artificial Intelligence

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Thermal Imagery Feature Extraction Techniques and the Effects on Machine Learning Models for Smart HVAC Efficiency in Building Energy

Cited by 12 publications

References 36 publications

Economy and elderly population, complementary or contradictory: A cross-continental wavelet coherence and cross-country Granger causality study

Economy and elderly population, complementary or contradictory: A cross-continental wavelet coherence and cross-country Granger causality study

Hybrid Statistical and Texture Features with DenseNet 121 for Breast Cancer Classification

Machine Learning Techniques to Predict Real Time Thermal Comfort, Preference, Acceptability, and Sensation for Automation of HVAC Temperature

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