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404 articles for “complex algorithms”
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A Review of Constrained Association Rule Mining
Abstract: Market basket analysis is a topic of concern when Apriori was developed. By the time, the algorithms are evolving and focusing on reducing complexity, number of database scans, using certain checking to generate only useful rules. For generating rules, firstly by support value, algorithms can extract frequent itemsets. After specifying confidence certain rules are generated. Because of generating buying pattern, a large number of areas are using association rule as …
Published in Journal of Web Engineering & Technology · Vol. 2, Issue 2, 2015 · pp. 18–22 Read article
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
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Synthesis of Coupler Curve on Optimizing a Four-Bar Mechanism with Ternary Linkage Using Genetic Algorithm
Abstract: AbstractDesigning of an intricate shaped coupler curve requires assembling of complex synthesis process in relationship with the linkages of a mechanism. This work is an attempt to address curvilinear path synthesis problem on designing and optimizing a four-bar mechanism with ternary linkage whose coupler tip traces an in-demand curve with enhanced fitness level. Coupler-curve equations of the mechanism have been derived in relationship with the linkages; in the follow-up, a …
Published in Journal of Advancements in Robotics · Vol. 3, Issue 3, 2016 · pp. 9–22 Read article
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Effective Implementation of Apriori Algorithm to Develop a Suggestion System Based on Sales History Using Hadoop Environment
Abstract: AbstractThe need for comprehensive support system to analyze and predict the nature of the dynamic market based on the previous records is very vital in competent industries today. The data mining is a process of extracting implicit, previously unknown and potentially useful information from data. Mining is search for relationships and global patterns that exist in the large databases but that are hidden among vast amount of data. Since the …
Published in Journal of Advanced Database Management & Systems · Vol. 3, Issue 3, 2016 · pp. 8–16 Read article
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Structure–Property Modeling of Cement-Based Multi-Component Composites Using Ensemble Machine Learning and Explainable Feature Attribution
Abstract: Accurate prediction of compressive strength is central to structure–property optimization, quality control, and sustainability-driven design in cement-based composite materials. Cementitious systems represent heterogeneous multi-phase composites composed of reactive binder matrices and dispersed aggregate phases, whose macroscopic mechanical performance emerges from complex nonlinear interactions among constituents and curing-dependent microstructural evolution. This study develops a data-driven structure–property modeling framework to quantify the nonlinear dependence of compressive strength on multi-component composite composition and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 112–131 Read article
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Intuitionistic Fuzzy Hypergraph Laplacians and Dominating Transversals for Resilient Discrete Network Design
Abstract: This manuscript develops a discrete mathematical framework for resilience analysis on networks whose interactions are polyadic, uncertain, and partially conflicting. Classical graphs compress multi-way coordination into pairwise edges, while ordinary fuzzy graphs often ignore the non-membership information that becomes critical in emergency logistics, infrastructure interdependence, and cyberphysical coordination. We therefore formulate an intuitionistic fuzzy hypergraph in which each vertex hyperedge incidence carries membership, non-membership, and hesitation, and we construct a …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 15–21 Read article
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Record Linkage in Knowledge Discovery Process Using Angle Based Machine Learning
Abstract: Record linkage is a critical data cleansing step in the knowledge discovery process, aimed at identifying and resolving inconsistencies across datasets. This study proposes an enhanced record linkage framework tailored for uncertain and large-scale data using a combination of distance measurement, probabilistic modeling, and semantic reasoning. A novel angle-based distance measurement technique is introduced to optimize matching between candidate records. To further boost match accuracy, a Finite Mixture Model (FMM) …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1157–1170 Read article
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Fraudulent Data Detection of Credit Card by Using Random Forest Method to Calculate ROC and Confusion Matrix
Abstract: Credit card fraud defaults in trillions of dollars online merchants. Researchers have more and more complex methods of detecting fraud using algorithms for machine learning, but there are rare reports of hands-on implementations. We describe the implementation of an extortion discovery framework in a huge e-tail retailer. The paper looks at the combination of manual and robotized classification and offers experiences into the whole handle of advancement. The paper can …
Published in Journal of Advanced Database Management & Systems · Vol. 7, Issue 1, 2020 · pp. 15–22 Read article
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Comparative Analysis of Fuzzy C-Mean and Level Set Segmentation Method for Brain Tumor Classes
Abstract: AbstractImage analysis is very important for many methodologies to process and identify the information of biomedical images. The segmentation technique is used to detect and characterize the biomedical images. The understanding of patient disease problem is an important task for radiologists. In this paper, we have presented the Fuzzy C-Mean (FCM) method for an objective function with fitting value and the Level Set Method (LSM) used for initial seeds contour …
Published in Journal of Open Source Developments · Vol. 4, Issue 3, 2017 · pp. 1–8 Read article
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Optimization of Artifact Free Image Upscaling Using Genetic Algorithm
Abstract: Creating an upscaled image from a low-resolution (LR) image to high resolution (HR) is very interesting. The nature and texture of an image should be maintained during upscaling of an image. This upscaling is also termed as “super-resolution”. It is related to both, statistical relationships between low-resolution and high-resolution. Several methods have been proposed to obtain better results, involving simple heuristics, edge modeling or statistical learning. The most powerful ones, …
Published in Journal of Web Engineering & Technology · Vol. 7, Issue 1, 2020 · pp. 21–29 Read article
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Isogeometric Topology Optimization of Continuum Structures using Evolutionary Algorithms
Abstract: Isogeometric analysis is a popular method for the analysis of problems involving complex geometry and governed by differential equations. Meta-heuristics are widely used to determine the optimum distribution of material within the given design domain. The focus of this study is to perform isogeometric topology optimization of continuum structures using meta-heuristics nature inspired firefly algorithm. NURBS basis functions are used to construct the geometric model and to calculate the displacements …
Published in Journal of Experimental & Applied Mechanics · Vol. 8, Issue 3, 2017 · pp. 8–18 Read article
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Speeding Up Human Operability and Multi-Tasking Through Mobile Evolutionary Algorithm for Evasive Interactive GUIs of Semantic Desktop Application
Abstract: In this paper, we introduced an algorithm for new optimized method of interacting with Graphical User Interfaces (GUIs) which adds swiftness and evolve with the human operability thus, reducing the number of parameters from the edified Multi-task work process. We validate our algorithm based on the accountable general consensus and confidence data extracted through a number of user's work experience on our interactive GUIs; demonstrating that our algorithm adapts with …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 1, Issue 2, 2014 · pp. 8–11 Read article
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Cogeneration of Fast Motion Estimation Processor and Algorithms Using Loss Less Compression
Abstract: Flexible and scalable motion estimation processor for the h.264 advanced video coding standard handling the processing requirements for high-definition video and suitable for Field-Programmable Gate Array (FPGA) implementation. The new motion estimation algorithm of kalman filter used to reduce the computational complexity. The eight custom instruction sets are used in the motion estimation. All processor instances are remaining binary compatible so recompilation process is not required. The motion estimation algorithm …
Published in Journal of VLSI Design Tools and Technology · Vol. 3, Issue 2, 2013 · pp. 1–5 Read article
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Evolutionary Particle Swarm Optimization (EPSO) based technique considering Voltage Stability Margin for Reactive Power Reserve Optimization
Abstract: Reactive power reserve and voltage stability are one of the important parameters required for proper operation of the electrical power system. Voltage stability covers a broad span of phenomena in power systems and its applications. Voltage stability is defined as ability of power system to assist fixed bearable potential at every single bus of the system under standard operating conditions and when put through to a disturbance. At any instant …
Published in Journal of Power Electronics and Power Systems · Vol. 11, Issue 2, 2021 · pp. 36–41 Read article
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A Novel Register Minimization Technique for Efficient Implementation of BLMS Filter
Abstract: Purpose: This paper presents a novel register minimization technique for the BLMS filter. The purpose is to reduce the number of registers leading to reduction in hardware resource used for BLMS filter and thus reducing the complexity. Design/Methodology/Approach: In the BLMS filter due to substantial number of register and hardware resource, Strassen’s algorithms are used to minimize the registers. Strassen’s algorithm is used for the matrix multiplication in the BLMS …
Published in Journal of Microelectronics and Solid State Devices · Vol. 4, Issue 2, 2017 · pp. 18–31 Read article
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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Sustainable Cotton Crop Productivity through Precision Weed Detection: A Deep Learning-Based Approach with UAV Integration
Abstract: Weeds present a major challenge to crop productivity by competing with crops for vital resources, including water, sunlight, and nutrients, often resulting in significant yield reductions. On a global scale, weeds are responsible for approximately 13.2% of annual crop losses, a quantity sufficient to feed nearly one billion people. These invasive plants disrupt agricultural systems and adversely impact crop yields. Given their uneven distribution in fields, ground or aerial robots …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 19–26 Read article
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Data-driven Approaches to Mineral Resource Management Using AI: A Brief Review
Abstract: The role of Artificial Intelligence (AI) in the mineral resource sector has become increasingly significant over the past few years, as industries seek to optimize and modernize their operations. AI encompasses a variety of technologies and techniques, such as machine learning, deep learning, and expert systems, that are now widely used in mineral exploration, resource estimation, and mine management. These AI-driven approaches have brought about a transformative shift, enhancing efficiency, …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 25–29 Read article
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Efficient Energy Management using Artificial Intelligence (AI) and Machine Learning (ML) in Chemical Industry
Abstract: The globe is moving toward higher usage of renewable energy sources, particularly solar and wind energy, as a result of depleting fossil fuel supplies and growing environmental concerns. There are several forecasting methods available for effective wind energy utilization. This review uses algorithms for predicting solar and wind energy as well as artificial intelligence (AI) techniques. A wind-coal coupling energy system planning scheme was designed to lower the high energy …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 2, 2025 · pp. 33–50 Read article
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A Next-Generation IoT-Enabled Smart Cane for the Visually Impaired: Integration of Advanced Navigation, Context-Aware Obstacle Detection, and Real-Time Voice Guidance
Abstract: The rapid growth of Internet of Things (IoT) technologies, combined with advances in embedded systems and artificial intelligence, has opened new possibilities for developing assistive mobility solutions tailored to the needs of individuals with visual impairments. This paper introduces an IoT- enabled smart cane designed to enhance independent mobility through intelligent environmental interpretation and context-aware navigation. Unlike traditional canes that rely solely on tactile feedback, the proposed system incorporates multiple …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 1, 2026 · pp. 12–17 Read article