Опубликована: Сен. 18, 2024
Язык: Английский
2018 5th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), Год журнала: 2023, Номер unknown, С. 101 - 105
Опубликована: Дек. 1, 2023
Remote sensing technology has been a crucial tool for gathering information about the Earth's surface and atmosphere many years, with applications spanning several fields such as agriculture, forestry, coastal zone management, environmental monitoring. This article presents comprehensive overview of remote principles their uses in various industries. The fundamental concepts sensing, including electromagnetic radiation, sensors, platforms used data collection, image processing techniques, are discussed. Moreover, different types data, multispectral, hyperspectral, SAR explored along across Lastly, challenges possibilities examined, future prospects
Язык: Английский
Процитировано
3
2018 5th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), Год журнала: 2023, Номер unknown, С. 959 - 963
Опубликована: Дек. 1, 2023
The investigation is centered to create a methodology utilizing an artificial neural network (ANN) forecast concrete's crushing resistance at the 28-day mark incorporating nanosilica offering as alternative traditional cement. Nanosilica commonly used construction material known for its ability enhance strength of concrete. Nevertheless, accurately predicting this requires intricate computations, consumes time, and demands expertise. To address this, AI model was created using machine learning algorithms, trained on dataset comprising experimental compressive data nanosilica-concrete mixtures, along with additional information particle properties. model's efficacy assessed independent dataset, which demonstrated nanosilica's high precision. objective research use ANN technique establish link between various input factors resultant in nanosilica-containing utilized study sourced from existing literature.
Язык: Английский
Процитировано
1
2018 5th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), Год журнала: 2023, Номер unknown, С. 147 - 151
Опубликована: Дек. 1, 2023
Stock market prediction is a difficult yet crucial task that has piqued the interest of both academics and investors. Due to their capacity process analyze huge chunk data in real-time, algorithms based on machine learning have become an effective tool for predicting stock values. We explore usage different approaches this research, including decision trees, random forests, support vector machines, neural networks, deep techniques. cover benefits drawbacks each algorithm, as well its applicability various sorts roots such finance/business records, news articles, social media. additionally look at difficulties come with using prediction, overfitting, quality, comprehensibility. Lastly, we describe some recent research employed anticipate equity markets, assess effectiveness practical utility. Overall, study gives thorough review state art algorithms, identifying significant obstacles potential interesting area.
Язык: Английский
Процитировано
1
2018 5th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), Год журнала: 2023, Номер unknown, С. 1287 - 1291
Опубликована: Дек. 1, 2023
Lung cancer is the foremost global health concern crossways world and various people die due to this disease because symptoms are visible at last stages of cancer. Detection timely accurately plays a vital role for taking action improve patient's health, if it not detected in early stages, chance survival rate very less. To overcome problem, now days, use Artificial Intelligence (AI) helps diagnosis lung stage. In work, we trained deployed Feed Forward Neural Network (FF-ANN) tuned with optimizers diagnose Various parameters used ANN algorithm using evaluated on cancers datasets. Accuracy proposed model best Adam optimizer comes out be 97.6%.
Язык: Английский
Процитировано
1
2018 5th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), Год журнала: 2023, Номер unknown, С. 442 - 445
Опубликована: Дек. 1, 2023
In recent decades, there has been a notable emphasis on wireless sensor network data collecting due to the growing demand of data-gathering through WSNs as result Internet Things (IoT) popularity. However, attaining best possible performance is severely hampered by resource constraints devices. This study presents solution this problem proposing Greening Wireless Sensor Networks, which considers two different energy levels (normal and advanced) nodes. this, count advanced nodes calculated rationally distributed appropriately. Normal nodes, other hand, are haphazardly placed next Advanced forward base station (BS) using chain-based transmission. proposed methodology helps save significant amount result. A variety criteria considered assess network's performance, protocol can outperform popular routing protocols.
Язык: Английский
Процитировано
1
Algorithms for intelligent systems, Год журнала: 2024, Номер unknown, С. 177 - 190
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
0
Опубликована: Сен. 18, 2024
Язык: Английский
Процитировано
0
Опубликована: Сен. 18, 2024
Язык: Английский
Процитировано
0
Опубликована: Сен. 18, 2024
Язык: Английский
Процитировано
0
Опубликована: Сен. 18, 2024
Язык: Английский
Процитировано
0