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124 articles for “hybrid algorithm”
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Bridging Brain-Inspired Learning and Quantum Reasoning for Future AGI Systems
Abstract: This research paper presents a novel neuromorphic–quantum hybrid computing framework envisioned to advance intelligent systems toward artificial general intelligence. The architecture integrates brain-inspired spiking networks for adaptive, energy-efficient learning with quantum processors for non-classical optimization and reasoning. A shared synaptic–quantum memory layer enables dual information representation, while neuromorphic adaptive controllers provide real-time stabilization of noisy quantum circuits. While quantum processors offer features like superposition- enabled exploration and entanglement-based correlations that …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 · pp. 1–9 Read article
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Temperature Control System using Artificial Intelligence
Abstract: Artificial Intelligence (AI) based controller for temperature control of a water bath system. The generation of membership function is a changeling problem for fuzzy systems and the response of fuzzy systems depends mainly on the membership functions. Artificial Neural Network based input and output used to tune the membership functions in fuzzy system. Two input and single output artificial intelligence is designed to control the temperature system .Further the tuning …
Published in Journal of Control & Instrumentation · Vol. 3, Issue 1-3, 2012 · pp. 76–83 Read article
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Enhancing Production Line Efficiency: Simulating and Optimizing Single and Parallel Line Processes
Abstract: During a time of fast-paced industrial growth, increasing production line effectiveness is a core issue for manufacturers looking to maximize output, reduce waste, and stay competitive. This study explores the use of simulation-based optimization methods to enhance single and parallel production line designs. Stepping beyond traditional trial-and-error methods, the research utilizes Siemens Tecnomatix Plant Simulation to simulate actual manufacturing scenarios, considering intricacies like buffer capacities, machine sequencing, and event-driven scheduling. …
Published in Journal of Production Research & Management · Vol. 15, Issue 1, 2025 · pp. 22–32 Read article
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Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 10–20 Read article
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A Novel Algorithm for an Optimal Reconfiguration of a Power Distribution System
Abstract: This paper presents a new optimization method based on the Hybrid Symbiotic organism Search Algorithm (HSOS) for the reconfiguration of a power distribution network for minimizing active power losses and maximizing voltage at each node. The HSOS method is a new metaheuristic algorithm that improves the Symbiotic organism Search (SOS) algorithm. This new technique is a combination of the SOS and the PSO (Particle Swarm Optimization) algorithm. It is applied …
Published in Journal of Power Electronics and Power Systems · Vol. 10, Issue 1, 2020 · pp. 9–17 Read article
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Power Quality Monitoring in Wind Solar Hybrid System
Abstract: With the development of new functionalities, solar and wind energy based hybrid systems are upcoming energy source with higher efficiency. Solar and wind energy being naturally available in abundance and non-polluting, is one of the most promising sources. Due to the development of modern power electronic devices, the power quality of wind solar hybrid system gets affected. Hence, due to the increasing usage of sensitive electronic equipments in wind solar …
Published in Journal of Power Electronics and Power Systems · Vol. 8, Issue 1, 2018 · pp. 16–23 Read article
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A Survey On Leveraging Machine Learning for Phishing Attack Prediction and Detection
Abstract: Phishing is one of the biggest cybersecurity threats that exploits user trust by masquerading as a legitimate site or email to steal personal and sensitive information. A state- of-the-art-phishing detection systems survey, this review showcases the evolution from traditional list-based techniques, including blacklisting and whitelisting to machine learning and deep learning models. While list-based systems cannot evolve to detect new and zero-day attacks, the ML algorithms of Decision Tree, Random …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 1–10 Read article
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Fraud Detection in Government Procurement Using Machine Learning
Abstract: Fraud represents a significant challenge in the realm of procurement, with estimates indicating that between 12 and 30% of global procurement budgets are lost to fraudulent activities (OECD, 2023). The pervasive nature of procurement fraud, which may encompass a range of deceptive practices such as bid rigging, invoice fraud, and procurement kickbacks, not only undermines the integrity of financial operations but also results in substantial losses for organizations. These losses …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 19–34 Read article
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Hybrid Approach for Community Detection Using Deep Learning Techniques
Abstract: Community detection in complex networks is a fundamental problem with applications across diverse domains, ranging from social networks to biological systems and beyond. Traditional methods based on graph theory have been widely used for identifying communities within networks. However, the intricate and evolving nature of modern networks demands more sophisticated approaches. This research work proposes a hybrid approach that combines the strengths of deep learning techniques with traditional community detection …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 3, 2024 · pp. 18–26 Read article
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Numerical Simulation of Hybrid GSA Based Optimal Power Flow for Multi Objective Optimization Strategy
Abstract: Restricted nonlinear optimization in electric power systems engineering is a topic of Optimal Power Flow (OPF) that has been extensively investigated. It has been a long and remarkable history for the OPF, which was founded in the 1960s, of research and publication. Newcomers to OPF research face a challenging undertaking since there is so much information available and because OPF's popularity within the electric power systems community has prompted authors …
Published in Journal of Instrumentation Technology & Innovations · Vol. 11, Issue 3, 2021 · pp. 24–32 Read article
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Comparative Study of Structure-from-Motion Algorithms 3D Shape Reconstruction
Abstract: 3D shape reconstruction from multiview photographs and video sequences (2D images) is an active area of research. Existing face recognition systems are based on 2D facial images and exhibit well-known deficiencies. Accordingly, the face recognition research is gradually shifting from classical 2D to sophisticated 3D or hybrid 2D/3D. Currently the 3D reconstruction algorithms may be grouped in to four categories. These are shape-from-X, 3D morphable model (3DMM), structure from motion …
Published in Current Trends in Signal Processing · Vol. 6, Issue 1, 2016 · pp. 1–10 Read article
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AI-Assisted Optimization of Supersonic Airfoil Shapes Using CFD Coupling
Abstract: This paper presents a novel framework for optimizing supersonic airfoil geometries through integrated artificial intelligence and computational fluid dynamics coupling. Traditional gradient-based optimization methods for high-speed aerodynamic shapes suffer from computational expense and convergence difficulties in non-convex design spaces. The proposed methodology employs a deep neural network surrogate model trained on high-fidelity Reynolds-Averaged Navier-Stokes solutions to approximate aerodynamic performance metrics across the design space. A hybrid particle swarm-genetic algorithm searches …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 8–17 Read article
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A Review of AI-Based Intrusion Detection Systems for Mobile Ad Hoc Networks (MANETs)
Abstract: Mobile Ad Hoc Networks (MANETs) comprise wireless networks that lack any conventional infrastructure . Their chief features include highly changing network topologies, lack of centralized administration, and open nature of communication, which collectively result in making MANETs of the wireless kind very susceptible to a diverse range of cyber-attacks like blackhole, greyhole, wormhole, flooding, Sybil and denial-of-service (DoS) among others. Conventionally, Intrusion Detection Systems (IDS) relying on static rule-based methods …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Optimizing Tourist Mobility with Dijkstra’s Algorithm: A Review on Pollution Reduction through Smart Path Planning
Abstract: Although Tourism helps the economy, but it can also harm the environment, especially in popular tourist destinations. Optimizing routing is one way to reduce these environmental effects. This review paper examines how the well-known and traditional Dijkstra's method for shortest path computation is used to pollution management and support sustainable tourism. The study explores how intelligent traffic routing can minimize traffic congestion in environmentally sensitive areas and lower fuel consumption …
Published in Trends in Transport Engineering and Applications · Vol. 13, Issue 2, 2026 · pp. 20–29 Read article
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A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article
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Tracking of Maximum Power Point for SPV Systems
Abstract: AbstractThis paper presents the optimization algorithm based maximum power point tracking techniques. Optimization of output of shaded and un-shaded photovoltaic array under either it is static or dynamic whether condition is the primary goal of each MPPT techniques. There are various aspects of each MPPT techniques such as cost effectiveness, simplicity of hardware and software, its implementation, requirement of sensor, level of popularity, level of accuracy and its convergence speed. …
Published in Journal of Semiconductor Devices and Circuits · Vol. 6, Issue 3, 2019 · pp. 33–45 Read article
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Economic Efficient Dispatch Solution with Pollution Control Technique Using Genetic Algorithm
Abstract: In this paper, an attempt has been made to create a hybrid power system with the available sources of energy to generate power in most efficient, economical, emission-less and in a sustainable way. It is a continuation of the research article published in Trends in Electrical Engineering, 2016, volume 6, issue 1, 10–16p. It is important to utilize the renewable sources of power generation since the global power demand is …
Published in Trends in Electrical Engineering · Vol. 6, Issue 3, 2016 · pp. 32–43 Read article
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Entangled Shields: Securing Digital Systems in the Quantum Cryptographic Revolution
Abstract: Quantum computing utilizing principles of superposition and entanglement is poised to revolutionize the computational landscape, presenting unprecedented challenges and opportunities across various disciplines. Among these, cryptography stands at the forefront due to its reliance on computational hardness assumptions, which Quantum algorithms, such as Grover’s and Shor’s, can efficiently exploit. This study explores theoretical foundations and practical applications of quantum-safe cryptographic primitives, such as lattice-based cryptography, hash-based signature schemes, code-based systems, …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 33–43 Read article
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Advancements in K-Means Clustering: Boosting Algorithm Performance through Innovations
Abstract: K-Means clustering is a widely used unsupervised learning algorithm for partitioning a dataset into distinct clusters. Despite its popularity and simplicity, K-Means has several limitations, such as sensitivity to initial centroids, convergence to local minima, and inefficiency with large datasets. This paper reviews recent advancements aimed at addressing these challenges and enhancing the performance of the K-Means algorithm. Innovations include improved initialization methods, such as K-Means++, which significantly reduce the …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 30–37 Read article
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Digital Signature Verification Based on Biogamal, SHA and Elgamal Algorithms
Abstract: Nowadays, in our day-to-day life online services are playing a very crucial role. Online services also have some certain security challenges in communication network. Security aspects consists of confidentiality of data/information, authentication of users and integrity of data. To achieve all these parameters, the information must be digitally signed by the original sender and verified by the intended recipient. Thus, research digital signatures should be further developed to improve the …
Published in Trends in Machine design · Vol. 7, Issue 3, 2020 · pp. 17 21 Read article