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Academic literature on the topic 'Refined ABC Algorithm'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "Refined ABC Algorithm"

1

Lenin, K. "DECREASING ACTUAL POWER LOSS BY REFINED ABC ALGORITHM." International Journal of Research -GRANTHAALAYAH 5, no. 10 (2017): 63–71. http://dx.doi.org/10.29121/granthaalayah.v5.i10.2017.2269.

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Refined ABC algorithm (RABC) proposed in this paper to solve the optimal reactive power problem. An artificial bee colony (ABC) algorithm is one of copious swarm intelligence algorithms that employ the foraging behavior of honeybee colonies. To progress the convergence performance and search speed of finding the best solution RABC algorithm has been developed. The main objective in this problem is to minimize the real power loss and also to keep the variables within the specified limits. Proposed Refined ABC (RABC) algorithm has been tested in standard IEEE 118 & practical 191 bus test sys

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Dr.K.Lenin. "DECREASING ACTUAL POWER LOSS BY REFINED ABC ALGORITHM." International Journal of Research - Granthaalayah 5, no. 10 (2017): 63–71. https://doi.org/10.5281/zenodo.1039599.

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Refined ABC algorithm (RABC) proposed in this paper to solve the optimal reactive power problem. An artificial bee colony (ABC) algorithm is one of copious swarm intelligence algorithms that employ the foraging behavior of honeybee colonies. To progress the convergence performance and search speed of finding the best solution RABC algorithm has been developed. The main objective in this problem is to minimize the real power loss and also to keep the variables within the specified limits. Proposed Refined ABC (RABC) algorithm has been tested in standard IEEE 118 & practical 191 bus test sys

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3

Sun, Qiang, and Shupei Liu. "Locating abrupt disaster emergency logistics centres using improved artificial bee colony (IABC) algorithm." Science Progress 104, no. 2 (2021): 003685042110162. http://dx.doi.org/10.1177/00368504211016205.

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Emergency management is conceptualized as a complex, multi-objective optimization problem related to facility location. However, little research has been performed on the horizontal transportation of emergency logistics centres. This study makes contributions to the multi-objective locating abrupt disaster emergency logistics centres model with the smallest total cost and the largest customer satisfaction. The IABC algorithm is proposed in this paper to solve the multi-objective emergency logistics centres locating problem. IABC algorithm can effectively calculate the optimal location of abrup

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Ghaffar, Muhammad Arslan, Lei Peng, Muhammad Umer Aslam, Muhammad Adeel, and Salim Dassari. "Vehicle-UAV Integrated Routing Optimization Problem for Emergency Delivery of Medical Supplies." Electronics 13, no. 18 (2024): 3650. http://dx.doi.org/10.3390/electronics13183650.

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In recent years, the delivery of medical supplies has faced significant challenges due to natural disasters and recurrent public health emergencies. Addressing the need for improved logistics operations during such crises, this article presents an innovative approach, namely integrating vehicle and unmanned aerial vehicle (UAV) logistics to enhance the efficiency and resilience of medical supply chains. Our study introduces a dual-mode distribution framework which employs the density-based spatial clustering of applications with noise (DBSCAN) algorithm for efficiently clustering demand zones

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Saleh, Izzati, Nuradlin Borhan, and Wan Rahiman. "Smoothing RRT Path for Mobile Robot Navigation Using Bio-inspired Optimization Method." Pertanika Journal of Science and Technology 32, no. 5 (2024): 2327–42. http://dx.doi.org/10.47836/pjst.32.5.22.

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This research addresses the challenges of using the Rapidly Exploring Random Tree (RRT) algorithm as a mobile robot path planner. While RRT is known for its flexibility and wide applicability, it has limitations, including careful tuning, susceptibility to local minima, and generating jagged paths. The main objective is to improve the smoothness of RRT-generated trajectories and reduce significant path curvature. A novel approach is proposed to achieve these, integrating the RRT path planner with a modified version of the Whale Optimization Algorithm (RRT-WOA). The modified WOA algorithm incor

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Tang, Yu, Min Xu, Jie Yue, and Shixiong Zheng. "Torsional Stiffness Correction of the Split-Type Triple-Box Steel Box Girder Based on Refined Simulation." Advances in Civil Engineering 2021 (June 28, 2021): 1–14. http://dx.doi.org/10.1155/2021/3667239.

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Split-type steel box girders are widely used in long-span bridges because of their good wind-resistance performance. In the design stage, a simple finite element model is usually established based on the beam element for wind-resistance design. However, since the irregular cross-beams and diaphragms in the split steel box girder cannot be virtually established, the stiffness of the girder will be underestimated. To improve the accuracy in simulating stiffness of the split-type triple-box steel box girder (STSBG) with the beam element model (BEM), a correction is made to the initial beam elemen

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Wu, Ji, Linqi Huang, Binquan He, et al. "Research on Multi-Objective Ore Blending Optimization Based on Non-Equilibrium Grade Polymetallic Mine of Shizhuyuan." Minerals 12, no. 11 (2022): 1358. http://dx.doi.org/10.3390/min12111358.

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The ore blending of non-equilibrium grade polymetallic ore is affected by various factors such as mineral resources, production technology, and economic efficiency. Aiming at the problems of Shizhuyuan Polymetallic Mine being diverse in nature, uneven in size, having many mining points, with large grade fluctuation, this paper proposes an optimization method for ore blending based on an artificial bee colony (ABC) algorithm. A multi-metal and multi-objective ore-blending optimization model is established with the minimum fluctuation of ore grade, mining transportation cost, and production capa

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Yuan, Chenyang, Chunlei Li, Hao Huang, Weifeng Bai, and Yunfei Xie. "Numerical Simulation Study on the Constitutive Model of Fully-Graded Concrete Based on Statistical Damage Theory." Buildings 13, no. 10 (2023): 2412. http://dx.doi.org/10.3390/buildings13102412.

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A statistical damage model (SDM) of fully-graded concrete was created using statistical damage theory, based on the mechanical properties of axial tension and axial compression of the material. The SDM considers two damage modes, fracture and yield, and explains the intrinsic connection between the mesoscopic damage evolution mechanism and the macroscopic nonlinear mechanical behavior of fully-graded concrete. The artificial bee colony (ABC) algorithm was used to obtain the optimal parameter combination through an intelligent search of parameters εa, εh, εb and H in the constitutive model by t

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Deng, Xiaoyi. "An Efficient Hybrid Artificial Bee Colony Algorithm for Customer Segmentation in Mobile E-commerce." Journal of Electronic Commerce in Organizations 11, no. 2 (2013): 53–63. http://dx.doi.org/10.4018/jeco.2013040105.

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Customer segmentation can enable company administrators to establish good customer relations and refine their marketing strategies to match customer expectations. To achieve optimal segmentation, a hybrid Artificial Bee Colony algorithm (ABC) is proposed to classify customers in mobile e-commerce environment, which is named KP-ABC. KP-ABC is based on three famous algorithms: the K-means, Particle Swarm Optimization (PSO), and ABC. The author first applied five clustering algorithms to a mobile customer segmentation problem using data collected from a well established chain restaurant which has

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Melveetil, Visakh Chandran. "An Optimal Multi-Modal Approach for Stock Market Price Forecasting with Fused Sentiment Analysis for Real Time Data." International Journal for Research in Applied Science and Engineering Technology 12, no. 9 (2024): 1605–22. http://dx.doi.org/10.22214/ijraset.2024.64417.

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Abstract: This study presents an innovative fusion-based methodology that integrates real-time stock market technical indicators with news sentiment analysis from financial news feeds to enhance stock selection decisions. The proposed framework employs a Bidirectional Long Short-Term Memory (Bi-LSTM) model for forecasting stock prices and a Deep Neural Network (DNN) used in conjunction with transformer-based model for sentiment classification, both optimized through the incorporation of real-time datasets. To further refine feature selection, Artificial Bee Colony (ABC) and Firefly algorithms

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Conference papers on the topic "Refined ABC Algorithm"

1

Creveling, Jessica, та Cedric Hagen. "COMBINING A δ13CCARB CORRELATION ALGORITHM AND A REFINED RADIOMETRIC CHRONOLOGY TO ADVANCE PRECAMBRIAN (EDIACARAN) BASIN ANALYSIS". У GSA 2020 Connects Online. Geological Society of America, 2020. http://dx.doi.org/10.1130/abs/2020am-355524.

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Awid, Abdurrezagh, Chengjun Guo, and Sebastian Geiger. "Improved Simulation Efficiency for Optimising Inflow Control Device Completions Using Suitably Upscaled Models and Parallel Global Search Optimisation Techniques." In Abu Dhabi International Petroleum Exhibition & Conference. SPE, 2021. http://dx.doi.org/10.2118/208150-ms.

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Abstract Inflow Control Device (ICD) completions can improve well performance by adjusting the inflow profile along the well and reducing the influx of unwanted fluids. The ultimate aim of using ICD completions is to provide maximum oil recovery and/or Net Present Value (NPV) over the life of the field. Proactive ICD optimisation studies use complex reservoir models and high-dimensional nonlinear objective functions to find the optimum ICD configurations over the life of the field. These complex models are generated from fine scale detailed geological models to accurately capture fluid flow be

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Wu, Zizhang, Zhuozheng Li, Zhi-Gang Fan, Yunzhe Wu, Yuanzhu Gan, and Jian Pu. "Learning Monocular Depth in Dynamic Environment via Context-aware Temporal Attention." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/172.

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The monocular depth estimation task has recently revealed encouraging prospects, especially for the autonomous driving task. To tackle the ill-posed problem of 3D geometric reasoning from 2D monocular images, multi-frame monocular methods are developed to leverage the perspective correlation information from sequential temporal frames. However, moving objects such as cars and trains usually violate the static scene assumption, leading to feature inconsistency deviation and misaligned cost values, which would mislead the optimization algorithm. In this work, we present CTA-Depth, a Context-awar

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Reports on the topic "Refined ABC Algorithm"

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Horrocks, Ian, Ulrike Sattler, and Stephan Tobies. A Description Logic with Transitive and Converse Roles, Role Hierarchies and Qualifying Number Restrictions. Aachen University of Technology, 1999. http://dx.doi.org/10.25368/2022.94.

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As widely argued [HG97; Sat96], transitive roles play an important role in the adequate representation of aggregated objects: they allow these objects to be described by referring to their parts without specifying a level of decomposition. In [HG97], the Description Logic (DL) ALCHR+ is presented, which extends ALC with transitive roles and a role hierarchy. It is argued in [Sat98] that ALCHR+ is well-suited to the representation of aggregated objects in applications that require various part-whole relations to be distinguished, some of which are transitive. However, ALCHR+ allows neither the

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