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1332 articles for “Predictive Modeling”
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Neural Network Model Prediction: A prediction model for Toxin release in environment from E-Waste
Abstract: — There is an exponential increase in the use of electronic devices, especially mobile gadgets. Earlier people used to replace their gadgets only when they were damaged but it is not the case now. Damages are no longer the only reason for disposing of electronic devices, where technical worn out, new product features, better aesthetics and emotional value are having strong influences to the disposal of the devices. This paper …
Published in Recent Trends in Programming languages · Vol. 4, Issue 3, 2017 · pp. 16–20 Read article
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Model Predictive Control for a Distillation Column Model
Abstract: Model Predictive Control (MPC) is a multivariable control (requires specific handling of each input as coupling and interaction is of a far greater effect) and uses the internal dynamic model of the process, past control moves and an optimization cost function over the receding prediction horizon, to calculate the optimum control moves. In this paper, the relation between MPC parameters was studied on process constraints. Conical tank level single-input-single-output (SISO) …
Published in Journal of Mechatronics and Automation · Vol. 1, Issue 3, 2014 · pp. 11–19 Read article
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Predictive Modeling and Optimization of Tensile and Flexural Strength in FDM 3D Printing Using Decision Trees and Bayesian Optimization.
Abstract: This research investigates predictive modelling and optimization technique for the tensile and flexural strength of PlA (Poly Lactic Acid) in Fused Deposition Modelling (FDM) 3D printing. Employing Decision Trees and Bayesian Optimization enhances comprehension and control of 3D printing process. Precise model predicts PLA material properties based on input parameters. Methodology involves rigorous data preprocessing, encompassing, cleaning, transformation, and normalization. Hyperparameter optimization via grid search systematically explores configurations, optimizing model …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 203–214 Read article
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DFT/Data Guided Predictive Modelling of Absorption Maxima in the OLED Rubrene Derivatives
Abstract: This study investigates the optical properties of rubrene derivatives to develop an accurate predictive model for absorption maxima using computational chemistry and chemoinformatic techniques. We benchmarked various quantum chemical methods, identifying that the M06-2X/aug-cc-pVDZ method in dichloromethane (DCM) provided the strongest correlation with experimental data. Key molecular descriptors such as band gap, ionization potential, and electrophilicity index were calculated and analyzed using principal component analysis (PCA) to identify significant factors …
Published in International Journal of Cheminformatics · Vol. 4, Issue 1, 2026 · pp. 41–56 Read article
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An Overview Mechatronics Systems Design of Modelica-Based Model Predictive Control Strategies for CO₂ Heat Pump Systems
Abstract: The growing adoption of renewable energy technologies poses challenges to energy supply stability, necessitating increased flexibility in energy demand. This paper introduces a Modelica-based Model Predictive Control (MPC) strategy aimed at keeping the supply water temperature within the range of 55°C to 75°C while minimizing energy consumption and electricity expenses throughout a year. A comprehensive, high-fidelity model representing a school building in Oslo, Norway, was developed using Modelica and exported …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 1, 2026 · pp. 15–27 Read article
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An Investigation of Model Predictive Control in Self-driving Vehicles
Abstract: Autonomous vehicles, which are often known as self-driving automobiles or driverless cars, are vehicles that can navigate and operate without human intervention. They require efficient controllers capable of handling complexities, with reduced computational costs, and should handle multiple inputs and outputs simultaneously. Model predictive control (MPC) possesses all these characteristics which means it can be utilized effectively for the same purpose. MPC for autonomous vehicles proposes various ways of achieving …
Published in Trends in Electrical Engineering · Vol. 14, Issue 1, 2024 · pp. 40–50 Read article
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Implement Artificial Intelligence and Machine Learning for Engineering Design, Predictive Modeling, and Optimizing Polymer Nanocomposites
Abstract: Polymer nanocomposites are high performance engineered materials obtained by inclusion of nano-sized fillers into the polymer matrix to enhance mechanical, thermal, electrical, barrier and functional properties. However, the complex and non-linear interactions among polymer chemistry, nanofiller characteristics, filler concentration, dispersion, interfacial bonding and processing conditions make it challenging to anticipate and maximize their properties. Artificial intelligence (AI) and machine learning (ML) offer powerful data-driven solutions to these difficulties by establishing …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Experimental Analysis and Predictive Modeling of Mechanical Behavior in Epoxy Composites Reinforced with Waste Tyre Rubber Particles
Abstract: The disposal of end-of-life tyres poses a significant environmental and resource challenge owing to their large volumes and non-biodegradable nature. In this work, we explore the incorporation of waste tyre rubber particles (WTRP) into an epoxy resin matrix to develop sustainable polymer composites and examine their mechanical behavior both experimentally and through predictive modelling. Composites with differing epoxy: WTRP ratios (80:20, 75:25, 70:30 wt.%) and varying rubber particle mesh sizes …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1754–1765 Read article
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Data-driven Comprehensive Predictive Model Leveraging Market Insights and Topographical Factors for Crop Productivity and Profitability
Abstract: For global food security and economic expansion, the agricultural industry is essential. However, farmers face numerous challenges such as unpredictable weather patterns, soil degradation, and market volatility, which affect crop productivity and profitability. This article proposes a prediction model that leverages market trends and topographical factors to optimize crop productivity and maximize profits. The model is designed using machine learning techniques and takes into account variables such as soil type, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 2, 2023 · pp. 21–30 Read article
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Survey of Predictive Models for Safe Route Predicting Using Machine Learning Techniques
Abstract: Safe route prediction is essential for the well-being and security of individuals in urban and rural environments. Machine learning techniques leverage historical data, real-time information, and algorithms to estimate the safety levels of different routes. The objective of safe route planning is to minimize risks, including crime-prone areas and accidents, reducing potential harm, property damage, and emotional distress. However, challenges arise from the complex and dynamic nature of urban environments, …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 1, 2024 · pp. 13–22 Read article
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Sustainable Concrete Solutions: Chemically Predictive Modeling of Geopolymer Versus Ordinary Concrete in a Circular Economy
Abstract: Concrete is a fundamental structural material widely used in civil engineering projects. It plays a key role in various types of building structures, with its quality directly influencing the durability of the construction. This research focuses on assessing the current state of concrete construction, highlighting critical issues and technical aspects in the process, while emphasizing the importance of improving construction quality and management practices. Geopolymer concrete (GPC) presents a viable …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 170–192 Read article
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Advancing Grid Integration: Maximum Power Point Tracking-Based Model Predictive Current Control Technique for Photovoltaic Systems
Abstract: Tracking a PV system's maximum power point is necessary as demand for grid-connected solar systems rises, regardless of utility demand. Since the PV system's output is D.C., a converter serving as a middleman between the PV system and the D.C. link capacitor is necessary to track the maximum power at all loads. Since the firing angle of the IGBT in the boost converter is between 0 and 1 at maximum …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 1, Issue 2, 2023 · pp. 31–35 Read article
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AI-Driven Innovation in Biomaterials: Predictive Modeling and Design for the Future
Abstract: The integration of artificial intelligence (AI) is revolutionizing the field of biomaterials, paving the way for innovative approaches in their development and production. This paper examines the connection between AI and biomaterials, emphasizing the substantial impact of predictive modeling on the evolution of the field. By examining recent research and cutting-edge uses, the document shows how AI-powered predictive modeling has revolutionized biomaterial design, marking a period of unparalleled precision and …
Published in Trends in Machine design · Vol. 11, Issue 3, 2024 · pp. 25–35 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Predictive Modeling System for Automated Skin Lesion Classification Using Deep Neural Networks and Voting Ensembles
Abstract: Skin cancer is one of the most prevalent cancers globally. Early and accurate diagnosis is critical for timely treatment and improved prognosis. This study presents a predictive modeling system for automated classification of skin lesions from dermoscopic images using deep neural networks and voting ensemble techniques. A customized 16-layer convolutional neural network architecture is developed for feature learning from lesion images. The concept of horizontal voting ensemble is implemented by …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 29–35 Read article
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Feature Engineering in Modern Predictive Modeling: Techniques, Automation Frameworks and Emerging Trends
Abstract: Feature engineering plays a crucial role in developing reliable and high-performing predictive models. It involves transforming raw and unprocessed data into meaningful features that help machine learning algorithms achieve better accuracy and overall performance. Feature engineering is helpful in identifying hidden patterns, removing noise, and increasing the signal-to-noise ratio in data sets. Machine learning techniques have progressed remarkably over the years, and the effectiveness of these models largely depends on …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 2, 2026 · pp. 32–40 Read article
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Predictive Model to Monitor the Exponential Transport of Spirochaeta Influenced by oxygen deficit And dispersion on natural pond
Abstract: Predictive model were considered to monitor the deposition of Spirochaeta in natural pond, the study considered the system to monitor the accumulation or exponential growth rate influenced by predominant parameters in the study environment, the effect from oxygen deficit observed characteristic of Dissolved Oxygen Levels. This includes Dissolved oxygen concentrations that are constantly influenced by diffusion and aeration, including photosynthesis, respiration and decomposition. This also includes water equilibrates toward hundred …
Published in Recent Trends in Fluid Mechanics · Vol. 8, Issue 1, 2021 · pp. 22–33 Read article
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Predictive model of wind turbine rotor-blade deflection
Abstract: A simulation process has been developed to predict wind turbine rotor-blade deflection caused by gravity effects. The model is based on the rotor-blade segmentation in finite elements, each one considered as an independent structure. The simulation has been extended to n-elements to make a more precise approach to the real performance. The range of deformation has been determined for a wind turbine rotor-blade analysing the effects of forces that creates …
Published in Journal of Offshore Structure and Technology · Vol. 8, Issue 2, 2021 · pp. 49–63 Read article
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Model Predictive Control of Variable Speed Variable Pitch Wind Energy Conversion Systems
Abstract: A multiple-input, multiple-output model predictive control technique for variable-speed, variable-pitch wind turbines in the below-rated wind speed zone is proposed. The speed of the generator and power generated are regulated simultaneously by controlling the pitch angle of the wind turbine and the generator torque. This has the effect of extracting the maximum power from the wind for wind speeds below the rated value. Also, as the constraints are incorporated on …
Published in Journal of Aerospace Engineering & Technology · Vol. 13, Issue 2, 2023 · pp. 20–29 Read article
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Machine Learning Based Early Cataract Detection: A Predictive Modeling Approach
Abstract: Cataracts, characterized by dense cloudy areas in the eye’s lens, afflict more than 50% of elderly individuals, leading to impaired vision and potential blindness. Detecting cataracts at an early stage is crucial to facilitate simpler treatments, as neglecting the condition may necessitate complex eye surgery. To address this issue, we are creating a predictive system that identifies cataract disease by analyzing user-provided eye features. To achieve this, we leverage OpenCV, …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article