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450 articles for “forests”
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A Review on Various Approaches of Intrusion Detection System and Random Forest in Data Mining
Abstract: With the development in Information and Communication Technology (ICT), it have become a fundamental factor of human’s life. But this technology has brought lots of threats in cyber world. These threats increase the chances of network vulnerabilities to attack the structure in the network. DM based intrusion area techniques consistently fall into any of the two classes; anomaly detection and mistreat finding. In general course of DM alludes to extricating …
Published in Recent Trends in Programming languages · Vol. 5, Issue 1, 2018 · pp. 6–13 Read article
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Geospatial Analysis of Biomass Distribution in Relation to Topography, Disturbance and Biological Richness in Forests of Kumaun Himalaya
Abstract: Biomass in forests of Kumaun Himalaya has been estimated using field sampling and remote sensing technique. Spatial distribution of biomass has been mapped and analyzed with reference to the topography, disturbance and biodiversity regimes. Biomass obtained in Kumaun Himalaya has been categorized in different classes from low to high biomass values. High biomass class (> 400 t ha-1) and moderate biomass class (300-400 t ha-1) showed 72% and 67% area, …
Published in Journal of Remote Sensing & GIS · Vol. 12, Issue 2, 2021 · pp. 46–57 Read article
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Comparative Assessment of Tropical Basins in the Savanna and Rain Forest Ecological Zones for Crop Production in Nigeria
Abstract: AbstractThis paper reviews the precarious situation of agricultural production in Africa and Nigeria specifically, in line with the emerging concepts of geoinformatics, precision farming and sustainable agricultural intensification. To illustrate the feasibility of operationalising these concepts in Nigeria, Ikpoba and Orle River basins (that are of the rain forest and savannah ecological zones, respectively) were classified into land suitability zones for the optimum cultivation of maize, cassava, yam and oil …
Published in Research & Reviews : Journal of Ecology · Vol. 3, Issue 1, 2014 · pp. 1–14 Read article
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Land Use and Land Cover Analysis of Jharkhand Using Satellite Remote Sensing
Abstract: IRS P6 LISS III data was used to delineate different land use/land cover classes of Jharkhand using visual interpretation technique. Tone and texture were found most important for interpretation of different objects. A total of 42 classes of different land use/land cover categories were interpreted. Agricultural land with current fallow and forest areas dominated the landscape of Jharkhand by occupying 49% and 30% of total geographical area, respectively. Built-up (urban …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 1, Issue 1-3, 2012 · pp. 22–31 Read article
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DDoS Detection Using Cascade Correlation for Improving Network Resources in Cloud Environment
Abstract: Intrusion detection is critical for protecting network security from emerging cyber threats. This study describes a unique intrusion detection system (IDS) based on the Random Forest algorithm. Random Forests are used as an effective classifier to identify patterns linked with malevolent behaviour. This technique uses Random Forests to improve the accuracy and efficiency of intrusion detection systems. The suggested methodology's value is shown by its performance on the benchmark KDD …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 17–22 Read article
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Impacts of Climate Change and Anthropogenic Stressors on Marine Ecosystems: A Comparative Study of Coral Reefs, Kelp Forests, and Arctic Fjords
Abstract: The accelerating impacts of climate change and human activities are profoundly reshaping marine ecosystems, threatening biodiversity, and altering trophic dynamics. This study synthesizes recent research on the responses of marine flora and fauna to temperature fluctuations, ocean acidification, pollution, and overfishing, highlighting the cascading effects on primary production, nutrient cycling, and ecosystem resilience. Using a combination of field surveys, remote sensing data, and meta-analytical approaches, we quantified biodiversity shifts across …
Published in International Journal of Marine Life · Vol. 3, Issue 1, 2026 · pp. 17–24 Read article
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Hypertuning in Random Forest Model
Abstract: Regarding the part of the monetary climate and the entirety of data made each second, the conclusionmaking handle is switching and obtaining to be data-driven, particularly controlling the trade procedures set up in organizing to keep the competitive benefit. Be that because it may, without innovation, data examination would not be feasible, the cause why machine learning is seen as a trouble for advancement trades, particularly due to its ability …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 3, 2022 · pp. 1–11 Read article
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Phytosociological Analysis in Kumaun Himalaya using Satellite Remote Sensing with Special Reference to Woody Vegetation
Abstract: AbstractThe present study deals with phytosociological analysis of woody vegetation (tree layer and shrub layer) of different forest types occurring in Kumaun Himalaya, Uttarakhand. A total 12 forest types were mapped using multiseason satellite data of IRS-P6, AWiFS sensor. Sampling was carried out in all the forest types to characterize the structure of forests in terms of abundance, density and dominance at different sites. The field data from different sites …
Published in Research & Reviews : Journal of Ecology · Vol. 3, Issue 1, 2014 · pp. 20–30 Read article
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Vegetation Analysis in Kumaun Himalaya using Remote Sensing
Abstract: Vegetation and land use of Kumaun Himalaya was analyzed using remote sensing data. A total of 15 vegetation and land use classes were mapped, of which, eight vegetation types and seven land use categories were identified. Utilizing the knowledge of altitude bound distribution of vegetation digital elevation model (DEM) was used for the post-classification refinements. Forest spreads over 52% of total geographical area, while 48% of the total geographical area …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 3, Issue 1, 2014 · pp. 9–16 Read article
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Geospatial Analysis of Biomass in Lake Region of Kumaun Himalaya, Uttarakhand
Abstract: The present study includes vegetation and forest biomass mapping in the lake region of Kumaun, Uttarakhand, using IRS1C LISSIII satellite data. A total of 11 forest types including forest plantation were mapped, among various forest types analyzed, maximum area exhibited by Banj oak followed by Pine forest. Mean total above-ground biomass values were ranged between 52.1 and 402 t/ha. Mean crown cover and biomass values were computed for selected sites. …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 2, Issue 3, 2013 · pp. 1–12 Read article
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Genomic Selection for Grain Yield in Wheat Using Machine Learning on DArT Molecular Markers: A Comparative Evaluation Across Multi-Environment Trials
Abstract: Genomic selection (GS) predicts complex quantitative traits directly from genome-wide molecular markers, bypassing the need for extensive phenotypic trials and accelerating plant breeding cycles. We conducted a comparative evaluation of seven regression approaches — ridge regression (the machine-learning equivalent of RR-BLUP), Lasso, Elastic Net, Partial Least Squares, linear Support Vector Regression, Random Forest, and Gradient Boosting — for predicting grain yield from 1,279 Diversity Array Technology (DArT) molecular markers genotyped …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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Customer Churn Prediction Using ML Algorithms
Abstract: Comprehending customer churn is essential for businesses aiming to enhance and sustain customer relationships. This study introduces a machine learning approach aimed at forecasting customer churn by leveraging demographic and behavioral data. Our research involved developing predictive models using support vector machines (SVM), random forests, and decision trees, evaluating their efficacy using real-world data from the telecom industry. Our findings underscore that random forests consistently outperform SVM and decision trees …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 70–75 Read article
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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
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Building a Resilient Climate Regulatory Ecosystem for Nigeria
Abstract: Terrestrial ecosystems, which store more carbon than the atmosphere, are vital to influencing carbon dioxide-driven climate change. Climate and land-use change are critical and interlinked components of the Carbon budget in human-dominated landscape, using the InVEST model maps of land use and stocks in four Carbon pools (aboveground biomass, belowground biomass, soil, dead organic matter) are used to estimate the amount of Carbon currently stored in the landscape and the …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 11, Issue 2, 2020 · pp. 46–62 Read article
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Regional Bioenergy Planning for Sustainability in Himachal Pradesh, India
Abstract: Energy systems in mountainous regions are complex due to the wide variations in the availability and demand of energy resources. Mountain inhabitants are traditionally dependent on bioenergy resources such as fuel wood, agro, and animal residues to meet their energy requirements for heating, cooking, etc. However, depleting forest resources limits the availability of fuel wood while commercial sources such as LPG and kerosene fail to meet the domestic energy demands …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 2, Issue 1-3, 2012 · pp. 37–73 Read article
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Application of Remote Sensing and GIS Techniques for Decadal Change Detection of Mangroves along Tamil Nadu Coast, India
Abstract: Mangrove forests are among of the most productive and biologically important ecosystems of the world. The mangrove forests aids stabilize shorelines and reduce the devastating impact of natural disasters such as tsunamis and hurricanes. They also provide breeding and nursing grounds for marine and pelagic species, and food, medicine, fuel and building materials for local communities. Despite of its immense importance, it is declining due to increasing coastal population, urbanization …
Published in Journal of Remote Sensing & GIS · Vol. 7, Issue 1, 2016 · pp. 42–53 Read article
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Land Cover Change Assessment of Pakke Tiger Reserve (PTR), East Kameng District of Arunachal Pradesh
Abstract: Land cover change is a global concern and a major contributor to the degradation of biodiversity loss, more specifically in reserved forest areas. As the human population increases, the forest covers of unprotected areas are used up and slowly the protected areas are being intruded to meet the needs. Presently, such cases of land cover changes and biodiversity losses in protected areas have been reported from many parts of the …
Published in Journal of Remote Sensing & GIS · Vol. 9, Issue 1, 2018 · pp. 26–33 Read article
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Analysis of Plants uses in Kalsa Watershed, Western Himalayan Ecoregion, India
Abstract: AbstractThe study was carried out to analyze the different use of plants in the forest areas of Kalsa watershed. Sampling was carried out in different forest types to record the diversity of plant species. A total of 48 trees, 43 shrubs and 83 herbs species of 72 families were recorded in different forest types. These species were evaluated for different uses based on the literature survey, interview conducted with local …
Published in Research & Reviews : Journal of Ecology · Vol. 3, Issue 2, 2014 · pp. 1–9 Read article
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A Machine Learning Based Artificial Intelligence Model for Detecting Heart Illness
Abstract: This study centers around the improvement of an artificial intelligence- and computerized reasoning-based heart sickness determination framework. We exhibit how AI can help with foreseeing whether an individual will get cardiovascular infection. In this review, a Python-based application for medical care research is created since it is more reliable and helps track and lay out many kinds of well-being observing applications. We show information handling, which incorporates working with all …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 50–58 Read article
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Optimizing Heart Disease Prediction: Comparative Analysis of Machine Learning Algorithm for Early Detection
Abstract: The expanding realm of data analysis holds considerable importance in healthcare, particularly in the medical sector where forecasting heart disease is considered a complex endeavor. Early prediction of serious health conditions can be the determining factor between survival and fatality, with heart disease being one such critical health issue. Over the past decade, the main reason for death has been heart disease. Heart disorders come in many different forms, and …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 1–10 Read article