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120 articles for “linear regressions”
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Gradient Boosted Regression Tree Approach to Predicting Toxic Interactions on X and YouTube
Abstract: In the digital age, social media platforms play a vital role in facilitating user engagement, encompassing both positive interactions and avenues for negative, often harmful behaviors. Recognizing and addressing toxic exchanges is paramount to nurturing healthy online communities and preserving users’ well-being. This study introduces a novel method for identifying toxic interactions by utilizing Gradient Boosting Regression Trees (GBRT) algorithm, a machine learning approach renowned for its exceptional accuracy and …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 3, 2025 · pp. 7–14 Read article
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Feasibility of Optimized Heat Source Assisted Combustion in Solid Rocket Motors
Abstract: Advances in rocket propulsion have a predominant role in space exploration developments. As an active chemical propulsion system, the efficiency of operations depends largely upon the nature of the combustion process and related energy transfer. Modern rockets are well known to epitomizes a distinct area of propulsion assisted by external thermal source(s)/rocket boosters. The presence of external heat source(s) encourages high possibility of fire risk/ hazards, which can adequately threaten …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 7, Issue 3, 2018 · pp. 12–25 Read article
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Detecting Electronic Circuitboard Thermal Abnormalities with Dynamic Hypernumbers
Abstract: This paper introduces the algebra of data acquisition using dynamic hypernumbers used in predicting thermal abnormalities with a rapid forecasting algorithm. Algebraic rules are defined for monitoring data from multiple sources. Each data source is considered a dynamic receptive synchronized hypernumber for building the resulting dynamic hypernumber. The algebraic dynamic hypernumberdefinition is used to present a low-complexity algorithm for identifying the thermal state of an electronic circuit board. The algorithm …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 10, Issue 3, 2023 · pp. 10–24 Read article
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Parametric Quantile Regression using Quantile-based Asymmetric Family of the Distributions
Abstract: Quantile regression is used for finding the effects of covariates on different quantiles of the response variable. The contribution of this article is to develop a theory of quantile regression using the Quantile-based asymmetric (QBA) family (similar to GAMLSS for mean regression) and then apply the proposed approach for analyzing COVID-19 data. More precisely, we estimate regression quantiles and investigate the asymptotic estimators under a generalized linear modeling framework, but …
Published in Research & Reviews : Journal of Statistics · Vol. 11, Issue 3, 2022 · pp. 54–66 Read article
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Fake News Detection Using N-Gram Analysis and Machine Learning Algorithms
Abstract: Fake news is untrue information presented as news. Fake news easily spread than real news amongst social networking sites. Detection of fake news is an important emerging research area which is gaining popularity. The main challenge in fake news detection is limited availability of resources (datasets). This project work detects fake news using n-gram analysis and machine learning algorithms. Evaluation and comparison between two feature extraction technique namely Term Frequency …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 8, Issue 1, 2021 · pp. 33–43 Read article
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Prediction of Traffic using Economic Attributes
Abstract: AbstractIncrease in traffic flow in a region reflects the development of transport infrastructure. Transport infrastructure development arises due to new investment in the region as it is a significant factor for assessing the social and economic viability of any highway project. Impact of economics on traffic is difficult to analyze traffic flow projection. To comprehend the objective, economic attributes such as investment and employment generated in the region are considered …
Published in Trends in Transport Engineering and Applications · Vol. 5, Issue 1, 2018 · pp. 32–36 Read article
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Comparative Study of Aggregate and Disaggregate Traffic Forecasting Technique for Industrial Corridor: Case Study of Vadodara District
Abstract: AbstractTransportation occupies a prominent place in modern life and its impact is spread in all domains of life. Transport planning is a discipline to study problems rising while planning transport facilities at urban, regional or national level and to prepare efficient basis for providing such facilities. Aim of transport planning at regional level is provision of connectivity and circuity with other regions as well as for expansion of existing facility …
Published in Trends in Transport Engineering and Applications · Vol. 5, Issue 1, 2018 · pp. 14–21 Read article
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Utilization of Statistical Learning Algorithms for Prediction of Elastic Modulus of Jointed Rock Mass
Abstract: This study uses two statistical learning algorithms for the prediction of elastic modulus (Ej) of jointed rockmass. The first algorithm uses support vector machine (SVM) that is firmly based on the theory of statisticallearning and uses regression technique by introducing -insensitive loss functionhas been adopted. Thesecond algorithm uses relevance vector machine (RVM). It is based on a Bayesian formulation of a linearmodel with an appropriate prior that results in a …
Published in Recent Trends in Civil Engineering & Technology · Vol. 1, Issue 1-3, 2011 · pp. 81–94 Read article
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Comparative Growth and Condition of Liza grandisquamis from Elechi and Amadi-Ama Creeks, Port Harcourt, Nigeria
Abstract: Growth and condition of Liza grandisquamis was assessed in two natural environments to create baseline information for accessing the fish stock. Regression analysis using the power curve W=aLb indicated a negative allometric growth in both water bodies. The difference in coefficient of growth for the two water bodies was not significant. Linear relationship between the length and weight variables was similar. Condition factors for the water bodies were significantly different …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 9, Issue 3, 2019 · pp. 1–4 Read article
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Implementation of Anticipating Rainfall Using Machine Learning
Abstract: Rainfall forecasting is crucial for many aspects of our national economy and should help prevent major seasonal droughts. Since agriculture is a beloved profession in many states, some Asian countries are economically hooked to decline. Previous precipitation info is beneficial. Farmers are cancerous in managing their crops, resulting in economic progress for the country. downfall prediction is hard for earth science scientists because of unordering time and unordered quantity of …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 1, 2023 · pp. 1–8 Read article
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SpecForesight: A Predictive Analytics Pipeline for Laptop Price Forecasting
Abstract: This paper frames laptop pricing as a supervised predictive analytics problem, transforming product specifications into feature-rich signals to forecast price with calibrated regression models and operational guardrails against drift. A structured pipeline ingests tabular listings, performs data cleaning, and engineers domain-informed features (e.g., central processing unit (CPU) family and clocks, graphics processing unit (GPU) tiering, memory/storage density, display, and touch capabilities), followed by encoding and normalization to optimize model learnability. …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 61–71 Read article
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Fault Diagnosis of Air Compressor (AC) System using Local Mean Decomposition (LMD) and Logistic Regression (LR) Machine Learning Classifier
Abstract: This article presents a detailed and systematic procedure for performing fault diagnosis in an air compressor (AC) system by analyzing the audio signals generated during its operation. The analysis covers both normal (healthy) conditions and seven distinct types of faults, including bearing failure, flywheel malfunction, inlet valve leakage, outlet valve leakage, non-return valve failure, piston ring defect, and rider belt issues. To acquire the acoustic signals, the researchers utilized a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 416–427 Read article
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The Role and Influence of Emotional Intelligence in Shaping Job Crafting: An Empirical Study
Abstract: The project titled "The Role and Influence of Emotional Intelligence in Shaping Job Crafting: An Empirical Study" explores the significant influence of Emotional Intelligence (EI) on job crafting while also examining how demographic factors impact this relationship. In today’s evolving workplace, employees are increasingly reshaping their roles to align better with their skills, values, and motivational process known as job crafting. Emotional intelligence, which includes the capacity to identify, comprehend, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 2, Issue 2, 2024 · pp. 15–23 Read article
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Seasonal Variation of Electric Vehicles Autonomy: Application to AC/DC Dual Voltage Operation
Abstract: In this work, a study to predict battery performance and autonomy for a dual type of electric engine, 480 VAC and 360 VDC, has been developed. The study has been conducted in vehicles of mass between 1000 and 3000 kg with battery capacity in the range of 40 to 100 kWh. The process has been simulated using reference values and modeled for specific driving conditions. The simulation has been developed …
Published in Journal of Mechatronics and Automation · Vol. 7, Issue 3, 2020 · pp. 1–15 Read article
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Statistical and AI Approaches to Measure Sustainability Performance of Enterprises
Abstract: Measuring sustainability performance has become a critical priority for enterprises facing increasing regulatory pressure, stakeholder expectations, and global sustainability challenges. Traditional assessment methods, largely based on static indicators and manual reporting, often struggle to capture the multidimensional, dynamic, and data-intensive nature of sustainability. This study explores the integration of statistical and artificial intelligence (AI) approaches to evaluate and enhance the sustainability performance of enterprises in a more robust, accurate, and …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 30–36 Read article
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Conceptualization of An Intelligent Decision Framework for Control Factors and Weld Quality Prediction
Abstract: To improve the robot's welding quality, control welding precision, optimize welding parameters, realize continuous welding quality database optimization, and increase welding defect detection, a fuzzy neural network-based intelligent decision-making system must be built. This study demonstrates how fuzzy control theory and BP neural networks may be used to identify welding issues and enhance process variables. The experimental findings indicate that, with seam classification accuracy close to 90%, enhancing welding parameters …
Published in Journal of Polymer & Composites · Vol. 11, Issue 6, 2023 · pp. 10–19 Read article
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A Geospatial Analysis of Correlation Between Built-up Area and Vegetation Coverage using Google Earth Engine in Saint Martin Island, Bangladesh
Abstract: Background: This study explores the complex interconnection between expanding human settlements and fluctuating plant life on the island of Saint Martin, Bangladesh, utilizing cutting-edge geospatial techniques through the open-source Google Earth Engine platform. The rapid population boom in Bangladesh and tourism-fueled development on Saint Martin Island stir serious worries about their ecological consequences. Methods: Remote sensing data sourced from Landsat 5 TM and Landsat 8 OLI/TIRS satellites between 1991 and …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 1, 2025 · pp. 21–29 Read article
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Machine Learning-Based Channel Estimation in 5G, Beyond-5G, and 6G Networks: Recent Advances and Future Directions
Abstract: Accurate channel estimation is one of the most fundamental challenges in modern wireless communication systems. In fifth- generation (5G) New Radio (NR) and emerging sixth-generation (6G) networks, precise knowledge of the wireless channel is essential for achieving reliable data transmission, high spectral efficiency, and low Bit Error Rate (BER). Conventional estimation techniques such as Least Squares (LS) and Minimum Mean Square Error (MMSE) rely on mathematical channel models and predefined …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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Advanced Modeling and Static Analysis of Inverted Umbrella Roof Shell Using ANSYS
Abstract: In this objective paper, an inverted umbrella roof shell are designing and modeling for the static analysis in ANSYS (15) using finite element method. The finite element analysis is carried by using total deformation and normal stresses in longitudinal direction and on X and Y plane to determine, respectively. Responses of umbrella roof shell results are linear and quadratic variation of the membrane displacements in the inverted direction are investigated …
Published in Journal of Structural Engineering and Management · Vol. 4, Issue 2, 2017 · pp. 31–35 Read article
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Comparison of RSM and ANN Modeling Approaches in Predicting the Laser Phase Transformation Hardening Parameters on the Heat Input and Hardened-Bead Profile Quality of Unalloyed Titanium
Abstract: In the present work, laser transformation hardening (LTH) of unalloyed titanium, nearer to ASTM Grade 3 of chemical composition was investigated using CW 2kW, Nd: YAG laser. The laser process variables such as laser power, scanning speed, and focused position play a major role in deciding the laser hardened bead quality. Two methods, Response Surface Methodology (RSM) and Artificial Neural Network (ANN) were used to predict the heat input and …
Published in Journal of Materials & Metallurgical Engineering · Vol. 5, Issue 1, 2015 · pp. 36–59 Read article