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9 articles for “temporal feature engineering”
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Controlled Temporal Feature Ablation and Explainable Ensemble Learning for Next- Hour Residential Electricity Forecasting
Abstract: Short-term residential load forecasting is increasingly used in demand response, home energy management, and data-driven grid operation, yet reported gains are often difficult to attribute to either the forecasting algorithm or the temporal representation supplied to it. This study presents a controlled, leakage-aware evaluation of temporal feature engineering for one-hour-ahead household electricity forecasting. The public UCI Individual Household Electric Power Consumption dataset was aggregated to hourly resolution, causally imputed using …
Published in Trends in Electrical Engineering · Vol. 13, Issue 3, 2023 Read article
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CIPHER Intelligence: AI-Powered Global Military Expenditure Analysis and Predictive Modeling
Abstract: Military expenditure analysis has emerged as a critical component of economic and geopolitical intelligence in the modern era. This paper presents CIPHER Intelligence, a comprehensive AI-powered platform for analyzing and predicting global military spending patterns across 211 countries spanning54 years (1970-2024). We employ advanced machine learning techniques, particularly Random Forest regression models, to achieve 99.5% prediction accuracy for military expenditure forecasting based on economic indicators. The platform integrates data from …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 1–8 Read article
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LightGBM-Based Grid Demand Estimation and Prediction for Intelligent Electricity Load Forecasting
Abstract: Correctly predicting electricity demand in emerging energy markets like India is the most effective way to maintain grid stability. This is particularly important. This article offers a comprehensive data- based structure that captures both the broad temporal dynamics and regional diversity. This technique utilizes a large-scale multi-dimensional feature space that includes temporal indicators, autoregressive lag terms, sliding-window rolling statistics, and state-level administrative markers. Our systematic benchmarking approach involves the use …
Published in Journal of Power Electronics and Power Systems · Vol. 16, Issue 3, 2026 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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AI-Driven IoT-Based Decision-Making System for Brainwave Study: The KSK Approach
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain–computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 28–35 Read article
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Integrated Polarimetric-Interferometric Fusion for Heterogeneous Urban Signature Extraction
Abstract: Mapping heterogeneous urban environments using conventional Synthetic Aperture Radar (SAR) backscatter intensity frequently produces classification errors due to spectral similarity between sparse built-up features, bare soil, and dry vegetation a challenge especially acute in semi-arid Deccan Plateau settings. This research presents a dual-path Pol- InSAR fusion framework that integrates polarimetric scattering decomposition and interferometric coherence stability to extract heterogeneous urban signatures over Beed Taluka, Maharashtra (area: 1,561.31 km²). A temporal …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 2, 2026 Read article
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Exploiting Phase of Speech Signal for Speaker Recognition
Abstract: Abstract—Performance of speaker recognition system with feature based on temporal phase is presented in this paper. In the state of the art spectral feature, Mel Frequency Cepstal Coefficient (MFCC) only magnitude of the Fourier Transform of speech signal is considered while phase is ignored. The cepstral coefficients extracted from temporal phase (MFTPC) of speech signal are used as features for speaker recognition system. The performance of MFTPC feature is evaluated …
Published in Journal of Communication Engineering & Systems · Vol. 9, Issue 2, 2019 · pp. 81–87 Read article
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Data-Driven Energy Forecasting for Smart Homes: Ensemble Learning from IoT Meters and Relevance for Polymer-Composite Based Smart Infrastructure
Abstract: Reliable estimation of household electricity demand is relevant in creating efficiency in energy usage, optimization of the loads, and intelligent demand-side management in intelligent grid systems. This paper introduces a varied machine learning model that approaches residential electric consumption prediction using an assortment of ensemble regression boosts, including Linear Regression, Lasso Regression, Decision Tree Regressor, Random Forest, and Gradient Boosting, to predict residential electricity consumption environments on a time-series arrested …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 29–64 Read article
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Recent Trends and Techniques in the Advanced Microcontroller Bus Architecture (AMBA) Protocol: A Comprehensive Review
Abstract: ARM has created the Advanced Microcontroller Bus Architecture (AMBA) that is used as the main method for communication on chips in today’s embedded systems. Since AMBA is built to scale and combine with other components, it allows data transfer to high-performance and low-power components easily. The paper discusses how AMBA protocols have evolved and presents new trends of producing higher data rates, conserving energy, and lowering latency. This study offers …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 3, 2025 · pp. 9–15 Read article