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Relevant bibliographies by topics / Hybrid SBF algorithm

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Academic literature on the topic 'Hybrid SBF algorithm'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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Journal articles on the topic "Hybrid SBF algorithm"

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Xiang, Shang, Gaobiao Xiao, and Junfa Mao. "Analyzing Electromagnetic Systems on Electrically Large Platform Using a GTM-PO Hybrid Method with Synthetic Basis Functions." International Journal of Antennas and Propagation 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/162421.

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A hybrid method of generalized transition matrix (GTM) and physical optics (PO) with synthetic basis functions (SBF) is proposed to analyze electromagnetic systems on electrically large platforms. Based on domain decomposition method (DDM), the proposed approach is to divide the whole problem into a GTM region and a PO region. The GTM algorithm can simulate antennas and scatterers accurately, and the PO algorithm is applied to obtain current distribution on the electrically large platform. With the characteristics extraction technique using SBFs on the GTM models, the number of unknowns can be

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Shaik, Asif Hussain, Chinna Babu Jyothi, Hasan Raza, and Mahmood Salman. "A hybrid soft bit flipping decoder algorithm for effective signal transmission and reception." TELKOMNIKA (Telecommunication, Computing, Electronics and Control) 20, no. 3 (2022): 510–18. https://doi.org/10.12928/telkomnika.v20i3.23300.

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The Euclidean geometry (EG) based low-density parity check (LDPC) codes are enciphered and deciphered in various modes. These algorithms have the back-and-forth between decoding delay, and power usage, device unpredictability resources, and error rate efficacy are all available with these methods. As a result, the goal of this paper is to develop a comprehensive method to describe both soft and burst error bits for optimal data transfer. As a result, for EG-LDPC codes, a hybrid soft bit flipping (HSBF) decoder is suggested, which decreases decoding complications while improving message data tr

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Akbarzadeh, Mohammad Reza, Hossein Ghafourian, Arsalan Anvari, Ramin Pourhanasa, and Moncef L. Nehdi. "Estimating Compressive Strength of Concrete Using Neural Electromagnetic Field Optimization." Materials 16, no. 11 (2023): 4200. http://dx.doi.org/10.3390/ma16114200.

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Concrete compressive strength (CCS) is among the most important mechanical characteristics of this widely used material. This study develops a novel integrative method for efficient prediction of CCS. The suggested method is an artificial neural network (ANN) favorably tuned by electromagnetic field optimization (EFO). The EFO simulates a physics-based strategy, which in this work is employed to find the best contribution of the concrete parameters (i.e., cement (C), blast furnace slag (SBF), fly ash (FA1), water (W), superplasticizer (SP), coarse aggregate (AC), fine aggregate (FA2), and the

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Kathirvel, Vigneshwer, Mohd Asyraf Mansor, Mohd Shareduwan Mohd Kasihmuddin, and Saratha Sathasivam. "Hybrid Imperialistic Competitive Algorithm Incorporated with Hopfield Neural Network for Robust 3 Satisfiability Logic Programming." IAES International Journal of Artificial Intelligence (IJ-AI) 8, no. 2 (2019): 144. http://dx.doi.org/10.11591/ijai.v8.i2.pp144-155.

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Imperialist Competitive algorithm (ICA) is a robust training algorithm inspired by the socio-politically motivated strategy. This paper focuses on utilizing a hybridized ICA with Hopfield Neural Network on a 3-Satisfiability (3-SAT) logic programming. Eventually the performance of the proposed algorithm will be compared to other 2 algorithms, which are HNN-3SATES (ES) and HNN-3SATGA (GA). The performance shall be evaluated with the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Sum of Squares Error (SSE), Schwarz Bayesian Criterion (SBC), Global Minima Ratio and Computation Time (CP

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Vigneshwer, Kathirvel, Asyraf Mansor Mohd., Shareduwan Mohd Kasihmuddin Mohd, and Sathasivam Saratha. "Hybrid imperialistic competitive algorithm incorporated with hopfield neural network for robust 3 satisfiability logic programming." International Journal of Artificial Intelligence (IJ-AI) 8, no. 2 (2019): 144–55. https://doi.org/10.11591/ijai.v8.i2.pp144-155.

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Imperialist Competitive algorithm (ICA) is a robust training algorithm inspired by the socio-politically motivated strategy. This paper focuses on utilizing a hybridized ICA with Hopfield Neural Network on a 3- Satisfiability (3-SAT) logic programming. Eventually the performance of the proposed algorithm will be compared to other 2 algorithms, which are HNN3SATES (ES) and HNN-3SATGA (GA). The performance shall be evaluated with the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Sum of Squares Error (SSE), Schwarz Bayesian Criterion (SBC), Global Minima Ratio and Computation Time (CP

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Fan, Mengting, Tsung-Hsien Wu, and Qizhi Zhao. "Assessing the Loss Given Default of Bank Loans Using the Hybrid Algorithms Multi-Stage Model." Systems 11, no. 10 (2023): 505. http://dx.doi.org/10.3390/systems11100505.

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The loss given default (LGD) is an important credit risk parameter in the regulatory system for financial institutions. Due to the complex structure of the LGD distribution, we propose a new approach, called the hybrid algorithms multi-stage (HMS) model, to construct a multi-stage LGD prediction model and test it on the US Small Business Administration (SBA)’s small business credit dataset. We then compare the model’s performance under four routes by different evaluation metrics. Finally, pertinent business information and macroeconomic features datasets are added for robustness validation. Th

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Rajagopal, Manikandan, Suvarna Buradagunta, Meshari Almeshari, Yasser Alzamil, Rajakumar Ramalingam, and Vinayakumar Ravi. "An Efficient Framework to Detect Intracranial Hemorrhage Using Hybrid Deep Neural Networks." Brain Sciences 13, no. 3 (2023): 400. http://dx.doi.org/10.3390/brainsci13030400.

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Intracranial hemorrhage (ICH) is a serious medical condition that necessitates a prompt and exhaustive medical diagnosis. This paper presents a multi-label ICH classification issue with six different types of hemorrhages, namely epidural (EPD), intraparenchymal (ITP), intraventricular (ITV), subarachnoid (SBC), subdural (SBD), and Some. A patient may experience numerous hemorrhages at the same time in some situations. A CT scan of a patient’s skull is used to detect and classify the type of ICH hemorrhage(s) present. First, our model determines whether there is a hemorrhage or not; if there is

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S, Pradeep. "A Novel HWRR-SJF Scheduling Algorithm for Optimal Performance Improvement in LTE System." International Journal of Engineering Education 1, no. 1 (2019): 1–8. http://dx.doi.org/10.14710/ijee.1.1.1-8.

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In currently, the revolution in a high-speed broadband network is the requirement and also endless demand for high data rate and mobility. To achieve above requirement, the 3rd Generation Partnership Project (3GPP) has been established the Long Time Evolution (LTE). LTE has established an improved LTE radio interface named LTE-Advanced (LTE-A) and it is a promising technology for providing broadband, mobile Internet access. But, better Quality of Service (QoS) to provide for customers is the main issue in LTE-A. To reduce the above issue, the packets should be utilized by using one of the most

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Mansouri, Deloula, Xiaohui Yuan, and Abdeldjalil Saidani. "A New Lossless DNA Compression Algorithm Based on A Single-Block Encoding Scheme." Algorithms 13, no. 4 (2020): 99. http://dx.doi.org/10.3390/a13040099.

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With the emergent evolution in DNA sequencing technology, a massive amount of genomic data is produced every day, mainly DNA sequences, craving for more storage and bandwidth. Unfortunately, managing, analyzing and specifically storing these large amounts of data become a major scientific challenge for bioinformatics. Therefore, to overcome these challenges, compression has become necessary. In this paper, we describe a new reference-free DNA compressor abbreviated as DNAC-SBE. DNAC-SBE is a lossless hybrid compressor that consists of three phases. First, starting from the largest base (Bi), t

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Ponomarchuk, Sergey, and Viktor Grozov. "Automatic interpretation of oblique sounding ionograms based on hybrid algorithms." Solnechno-Zemnaya Fizika 10, no. 2 (2024): 109–18. http://dx.doi.org/10.12737/szf-102202410.

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The paper presents a method of interpreting data on oblique ionosphere sounding (OS) with a continuous chirp signal. Hybrid algorithms for automatic interpretation of ionograms by selected points with significant amplitude obtained during secondary data processing for various heliogeophysical conditions have been developed and implemented. For the conditions of the two-layer ionosphere, an interpretation method has been worked out which involves analyzing histograms for the distribution of points with significant amplitude, which fall into a model mask constructed from the results of modeling

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Book chapters on the topic "Hybrid SBF algorithm"

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Gunasundari, S., and S. Janakiraman. "A Hybrid PSO-SFS-SBS Algorithm in Feature Selection for Liver Cancer Data." In Lecture Notes in Electrical Engineering. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-2119-7_133.

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Ould Sidi, Hamed, Rachid Ellaia, Emmanuel Pagnacco, and Ahmed Tchvagha Zeine. "An Immune Multiobjective Optimization with Backtracking Search Algorithm Inspired Recombination." In Search Algorithm - Essence of Optimization. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.100306.

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We propose a novel hybrid multiobjective (MO) immune algorithm for tackling continuous MO problems. Similarly to the nondominated neighbor immune algorithm (NNIA), it considers the characteristics of OM problems: based on the fitness values, the best individuals from the test population are selected and recombined to guide the rest of the individuals in the population to the Pareto front. But NNIA uses the simulated binary crossover (SBX), which uses the local search method. In our algorithm, the recombination is essentially inspired by the cross used in the backtracking search algorithm (BSA)

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Conference papers on the topic "Hybrid SBF algorithm"

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Cusumano, Linda, Rasmus Rempling, Nilla Olsson, and Mats Granath. "A Comparison Between Set-based Design and Genetic Algorithms for Cost and Carbon Optimization of Building Structures." In IABSE Symposium, Tokyo 2025: Environmentally Friendly Technologies and Structures: Focusing on Sustainable Approaches. International Association for Bridge and Structural Engineering (IABSE), 2025. https://doi.org/10.2749/tokyo.2025.1555.

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<p>Early structural design decisions significantly influence both cost and carbon emissions in construction projects. To understand the trade‐offs between costs and carbon emissions, the design team should incorporate carbon calculations already in the conceptual design phase and include several alternative designs. However, adding carbon as an optimization objective increases the complexity of the design process and requires more sophisticated evaluation methods. Therefore, this study evaluates two multi‐objective optimization approaches, Set‐Based Design (SBD) and Genetic Algorithms (G

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Fatima, Sabiya, Ramya I M, Ridhi Mayura Shivani R, Rajesh Kumar K, Jenitha T, and Amulya M P. "Hybrid Deep Learning Model for Prostate Cancer Detection Using LeNet and MobileNet V2 Algorithms." In 2025 International Conference on Computing for Sustainability and Intelligent Future (COMP-SIF). IEEE, 2025. https://doi.org/10.1109/comp-sif65618.2025.10969943.

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Reddy, Gajjala Venkat Rushith, Prayaga Shashank Abhiram, Ashwanth GPN, G. Surya Narayana, and Thangam S. "Improved Cluster-Based Data Aggregation in WSN for Efficient Data Transmission Using PEGASIS-TEEN Hybrid Algorithm." In 2025 International Conference on Computing for Sustainability and Intelligent Future (COMP-SIF). IEEE, 2025. https://doi.org/10.1109/comp-sif65618.2025.10969855.

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Natarajan, Durai Rajesh, Sreekar Peddi, Dharma Teja Valivarthi, Swapna Narla, Sai Sathish Kethu, and Dede Kurniadi. "Hybrid LSTM-GA and HS-CS Algorithms for Automation-Assisted Defect Identification in CNC Milling Robotics: Enhancing Global Search and Optimization." In 2025 International Conference on Computing for Sustainability and Intelligent Future (COMP-SIF). IEEE, 2025. https://doi.org/10.1109/comp-sif65618.2025.10969904.

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Tu, Yu, Kai Zhang, Yaoran Chen, Zhaolong Han, Yong Cao, and Dai Zhou. "A Comparison of Optimization Methods Applied to Surrogate-Based Optimization in Wind Farm Yaw Control." In ASME 2024 43rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/omae2024-125060.

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Abstract In wind farms, wake effects among turbines hinder optimal power generation, making collective yaw control crucial for efficiency. The accurate calculation of power generation for large-scale wind farm is time consuming and computationally expensive. To address this challenge, Surrogate-Based Optimization (SBO) emerges as an effective tool in the yaw optimization. In the design of experiment, wake effects are simulated by Gauss-Curl Hybrid (GCH) model in FLORIS. Based on the limited dataset, SBO utilizes surrogate models to approximate the relationship between yaw angles and total powe

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Nagel, Dieter, and Stephen Smith. "Using a hybrid data generator for testing of ABF-algorithms." In 2013 Workshop on Sensor Data Fusion: Trends, Solutions, Applications (SDF). IEEE, 2013. http://dx.doi.org/10.1109/sdf.2013.6698248.

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Martinez, Aldo, Hector Vargas, and Jose Perez. "An Evolutionary Software Engineering Approach Applied to a Hybrid Algorithm for Face Recognition." In 2012 Brazilian Robotics Symposium and Latin American Robotics Symposium (SBR-LARS). IEEE, 2012. http://dx.doi.org/10.1109/sbr-lars.2012.24.

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Pan, Min, Beichen Ding, Chenggang Yuan, Jun Zou, and Huayong Yang. "Novel Integrated Control of Fluid-Borne Noise in Hydraulic Systems." In BATH/ASME 2018 Symposium on Fluid Power and Motion Control. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/fpmc2018-8828.

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The noise in hydraulic machines presents itself as fluid-borne noise (FBN), structure-borne noise (SBN) and air-borne noise (ABN). FBN is caused by the unsteady flow produced by pumps and motors or the operation of digital hydraulics, and propagates through the system causing SBN, which in turn causes ABN. This article reports on a novel integrated FBN attenuation approach, which employs a hybrid control system by integrating an active feedforward noise attenuator with passive tuned flexible hoses. The passive hoses are tuned to cancel the high-frequency pressure pulsations, whilst the active

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