Search Results - (( variable remote learning algorithm ) OR ( java application sensor algorithm ))

Integration of machine learning and remote sensing for above ground biomass estimation through Landsat-9 and field data in temperate forests of the Himalayan region by Anees, Shoaib Ahmad, Mehmood, Kaleem, Khan, Waseem Razzaq, Sajjad, Muhammad, Alahmadi, Tahani Awad, Alharbi, Sulaiman Ali, Luo, Mi

“…While Landsat-9 provides reliable data crucial for long-term monitoring, it is part of a broader suite of available remote sensing technologies. We employ machine learning algorithms such as Extreme Gradient Boosting (XGBoost), Support Vector Regression (SVR), and Random Forest (RF), alongside linear regression techniques like Multiple Linear Regression (MLR). …”
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Estimating Forest Aboveground Biomass Density Using Remote Sensing and Machine Learning : A RSME Approach by Yaniza Shaira, Zakaria, Mohd Fadzil, Akhir, Aidy, M Muslim, Nur Afiqah, Ariffin, Azizul, Ahmad

“…The model's strong predictive performance (R2 = 0.77) implies that the independent variables accounted for 77% of the variability in the AGB. …”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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Design Of Robot Motion Planning Algorithm For Wall Following Robot by Ali Hassan, Muhamad Khairul

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Detection of mental disorders based on the analysis of emotion, facial expressions and facial movements in a video stream by Nurzhanova, Aizhan, Mussabek, Miras, Ince, Gokhan, Mustaffa, Mas Rina, Zhumadillayeva, Ainur

“…Using machine learning techniques and deep learning algorithms, we aim to create an algorithm for emotion recognition using a personalized approach. …”
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Human activity recognition via accelerometer and gyro sensors by Tee, Jia Lin

“…To implement the data engineering system proposed, two mobile applications, SensorData and SensorDataLogger with user-friendly interfaces and intuitive functionalities are developed using Java programming language and Android Studio. …”
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Improving forest above-ground biomass estimation by integrating individual machine learning models by Luo, Mi, Ahmad Anees, Shoaib, Huang, Qiuyan, Qin, Xin, Qin, Zhihao, Fan, Jianlong, Han, Guangping, Zhang, Liguo, Mohd Shafri, Helmi Zulhaidi

“…The accurate estimation of forest above-ground biomass (AGB) is crucial for sustainable forest management and tracking the carbon cycle of forest ecosystem. Machine learning algorithms have been proven to have great potential in forest AGB estimation with remote sensing data. …”
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Tree species and aboveground biomass estimation using machine learning, hyperspectral and LiDAR data / Nik Ahmad Faris Nik Effendi by Nik Effendi, Nik Ahmad Faris

“…Besides, Artificial Neural Network (ANN) and Random Forest (RF) algorithm was used to predicted the AGB using different combination of variables. …”
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Grid-based remotely sensed hydrodynamic surface runoff model using emissivity coefficient / Jurina Jaafar by Jaafar, Jurina

“…It is learned that creating an accurate description of the ground surface is a complex problem, which requires at least site study. …”
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Predicting wheat yield from 2001 to 2020 in Hebei Province at county and pixel levels based on synthesized time series images of Landsat and MODIS by Zhang, Guanjin, Roslan, Siti Nur Aliaa, Mohd Shafri, Helmi Zulhaidi, Zhao, Yanxi, Wang, Ci, Quan, Ling

“…In our study, the synthesized images of Landsat and MODIS were used to provide remote sensing (RS) variables, which can fill the missing values of Landsat images well and cover the study area completely. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

“…Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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Computational Thinking : Experiences of Rural Pupils in Sarawak Primary School by Nur Hasheena, Anuar

“…Although the quantitative data does not show promising results, the qualitative data can be used to support the learning experiences and knowledge acquired from the learning activities proposed. …”
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Design & Development of a Robotic System Using LEGO Mindstorm by Abd Manap, Nurulfajar, Md Salim, Sani Irwan, Haron, Nor Zaidi

“…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. Ultimately, the algorithm development program designed earlier is linked up directly to the robotic model for program implementation and verification. …”
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Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm by Ahmadi, Seyedeh Parisa

“…This study concluded that remote sensing approach combined with data mining approaches such as ANN algorithms have great potential in monitoring vast plantation areas in a rapid and inexpensive manner.…”
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Using satellite-measured relative humidity for prediction of Metisa plana’s population in oil palm plantations: a comparative assessment of regression and artificial neural network... by Ruslan, Siti Aisyah, Muharam, Farrah Melissa, Zulkafli, Zed, Omar, Dzolkhifli, Zambri, Muhammad Pilus

“…This study examined the relationship between the presence of Metisa plana at different time lags and remote sensing (RS) derived RH by using statistical and machine learning approaches. …”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

“…As the ALOS PALSAR-2 image was evaluated with dual-polarization (HH and HV), each digitized point has two distinct backscatter data with four severity levels (T0 to T3). The machine learning algorithm consistently performs well when presented with a well-balanced dataset. …”
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