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27th International Conference on Microelectronics (ICM)

作者： Jenkal, Wissam Latif, Rachid Toumanari, Ahmed Dliou, Azdine El B'charri, Oussama Ibn Zohr Univ ENSA Lab Syst Engn & Informat Technol Agadir Morocco

ISBN: (纸本)9781467387590

This paper aims at the detection of QRS position from the ECG signal using wavelet coefficients. An enhanced algorithm has been proposed in this work in order to approve the performance of QRS detection. This algorithm is based on three level, namely detection of suspect QRS regions, the discarding of false detected regions and the extraction of the highest peaks of the true QRS regions detected. This method has been tested on some of the MIT-BIH Arrhythmia database signals. The results of this method are promising in comparison with alternative methods recently published.

关键词： ECG Signals QRS complex wavelets coifficents enhanced algorithm

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A Underwater Image enhanced algorithm combined MSR and Channel Energy 22

A Underwater Image Enhanced Algorithm combined MSR and Chann...

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22nd IEEE International Conference on Advanced Communication Technology (ICACT)

作者： Yang, Yanying Xu, Xianwei Nanjing Forest Police Coll Nanjing 210023 Peoples R China

ISBN: (数字)9791188428045

ISBN: (纸本)9791188428045

Vision is the most important source of information for Unmanned Underwater Vehicle(UUV), only a clear image can make it possible for a UUV to operate automatically, Due to strong absorption and light scattering for water, the image of underwater imaging has a serious degradation, whether in distance or in quality. Based on classical Retinex theory, this paper proposed an underwater image enhanced algorithm. For different channel of underwater image has apparently different energy, especially green channel has overwhelming power than others, we added a step to energy balance of the RGB three channel in classical Multi-Scale Retinex (MSR). Experiment data show that, compared to the traditional three-channel simple addition, our improvement can get more natural recovered underwater image.

关键词： Channel energy enhanced algorithm Improvement MSR Underwater image

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enhanced algorithm for QRS detection using discrete wavelet transform (DWT)

Enhanced algorithm for QRS detection using discrete wavelet ...

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International Conference on Microelectronics

作者： Wissam Jenkal Rachid Latif Ahmed Toumanari Azdine Dliou Oussama El B'charri Laboratory of Systems Engineering And Information Technology ENSA Ibn Zohr University Agadir Morocco

关键词： ECG Signals QRS complex wavelets coifficents enhanced algorithm

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Optimizing proton exchange membrane fuel cell parameter identification using enhanced hummingbird algorithm

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2024年 89卷 342-352页

作者： Singla, Manish Kumar Safaraliev, Murodbek Gupta, Jyoti Aljaidi, Mohammad Odinaev, Ismoil Kumar, Ramesh Menaem, Amir Abdel Chitkara Univ Inst Engn & Technol Dept Interdisciplinary Courses Engn Rajpura Punjab India Ural Fed Univ Dept Automated Elect Syst Ekaterinburg 620002 Russia KR Mangalam Univ Sch Engn & Technol Gurgaon 122003 Haryana India Zarqa Univ Dept Comp Sci Zarqa 13110 Jordan Mansoura Univ Elect Engn Dept Mansoura 35516 Egypt Jadara Univ Jadara Univ Res Ctr Irbid Jordan Appl Sci Private Univ Appl Sci Res Ctr Amman Jordan

Fuel cells (FCs) have attracted significant interest due to their versatile applications, but modeling their nonlinear behavior is challenging. This research proposes an enhanced Artificial Hummingbird algorithm (EAHA) to identify the seven unknown parameters of proton exchange membrane fuel cell (PEMFC) stacks using their experimental data. The goal is to accurately predict the current/voltage (I/V) curves by minimizing a cost function defined as the sum of squared differences between measured data points and model estimates. The EAHA combines several territorial foraging techniques with a linear regulation mechanism. Its performance is compared to the conventional Artificial Hummingbird algorithm (AHA) using three common PEMFC modules. Additionally, a comparative analysis is performed against previously published methods and newly developed optimizers like Particle Swarm Optimizer (PSO), Grasshopper Optimization algorithm (GOA), Atom Search Optimization (ASO), Grey Wolf Optimizer (GWO), and parental algorithm i.e., Artificial Hummingbird algorithm (AHA). The findings showcase the proposed approach's efficacy relative to existing methods and state-of-the-art optimizers. The two models are taken for the checking of reliability and performance of the PEMFC. The results are also compared with the Non-Parametric tests and it is concluded that the proposed algorithm is far better than the rest of the compared algorithms in both the models.

关键词： Proton exchange membrane fuel cell Optimization Hydrogen enhanced algorithm Sum of square error Benchmark test function Non-parametric test

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Optimizing solar cell models: a multi-objective parameter estimation algorithm for improved photovoltaic system performance

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PHYSICA SCRIPTA 2025年第1期100卷

作者： Singla, Manish Kumar Aljaidi, Mohammad Gupta, Jyoti Safaraliev, Murodbek Kumar, Ramesh Ali, Ziad M. Alsharif, Mohammed H. Kim, Mun-Kyeom Saveetha Inst Med & Tech Sci Saveetha Sch Engn Dept Biosci Chennai 602105 India Zarqa Univ Dept Comp Sci Zarqa 13110 Jordan KR Mangalam Univ Sch Engn & Technol Gurgaon 122003 Haryana India Ural Fed Univ Dept Automated Elect Syst Ekaterinburg 620002 Russia Chitkara Univ Inst Engn & Technol Dept Interdisciplinary Courses Engn Punjab India Appl Sci Private Univ Appl Sci Res Ctr Amman 11931 Jordan Jadara Univ Res Ctr Amman Jordan Prince Sattam Bin Abdulaziz Univ Coll Engn Wadi Addawaser KSA Al Kharj 11991 Saudi Arabia Sejong Univ Coll Elect & Informat Engn Dept Elect Engn 209 Neungdong Ro Seoul 05006 South Korea Chung Ang Univ Sch Energy Syst Engn 84 Heukseok Ro Seoul 06974 South Korea

Accurate models of solar cells are required to improve the performance of solar photovoltaic (PV) systems. Due to a lack of precise parameters in the manufacturer's datasheet, the solar cell model is often inaccurate. Estimating the parameters needed improperly makes it impossible to build up a reliable solar PV cell model. This paper proposes an algorithm for estimating cell parameters by multi-objective optimization to solve this issue. Several optimizers attempted to address the suboptimal results of optimization due to local minima and premature convergence. This work aims to evaluate the effectiveness of the proposed algorithm with those other popular algorithms to understand its reliability. The efficiency of this algorithm is proven using empirical results and statistical figures. It has important features, including simplicity and high accuracy, which imply that the algorithm is better suited to estimating solar PV models when compared with other algorithms. This algorithm is robust as it is computationally efficient and easy to use, which makes this method applicable for solving a wide variety of problems related to solar energy.

关键词： mathematical modelling three diode model four diode model parameter extraction machine learning enhanced algorithm non-parametric test

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Enhancing music audio signal recognition through CNN-BiLSTM fusion with De-noising autoencoder for improved performance

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NEUROCOMPUTING 2025年 625卷

作者： Mao, Xiaoying Tian, Ye Jin, Tairan Di, Bo Soochow Univ Sch Music Suzhou 215123 Jiangsu Peoples R China Sichuan Conservatory Expt Arts Sch Chengdu 610021 Sichuan Peoples R China Sichuan Univ Coll Arts Chengdu 610207 Sichuan Peoples R China Zhejiang Normal Univ Sch Child Dev & Educ Hangzhou 310012 Zhejiang Peoples R China

This study presents an advanced framework for music audio signal recognition that combines Convolutional Neural Networks (CNNs), Bidirectional Long Short-Term Memory (BiLSTM) networks, and Noise Reduction Autoencoder models to significantly improve accuracy and robustness. The core innovation is a novel noise reduction auto-encoder that integrates CNN and BiLSTM architectures, enabling superior recognition performance under varying noise levels and environmental conditions. The proposed framework, validated on several datasets including the Zhvoice, Common Voice, and LibriSpeech, demonstrates higher accuracy compared to existing methods. In addition, an optimized CNN architecture called Faster Region-based CNN with Multi-scale Information (FRCNN-MSI) is developed for efficient speech feature extraction, which shows significant improvements in noisy environments. The BiLSTM model is further enhanced with an attention mechanism that improves sequence modeling and contextual relationship capture. Together, these advances establish our approach as a robust solution to real-world speech recognition challenges, with potential implications for improving speech recognition systems in diverse applications.

关键词： Audio signal enhanced algorithm Signal recognition CNN BiLSTM Fusion model De-noising auto-encoder

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An enhanced adaptive butterfly optimization algorithm rigorously verified on engineering problems and implemented to ISAR image motion compensation

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ENGINEERING COMPUTATIONS 2020年第9期37卷 3543-3566页

作者： Ustun, Deniz Tarsus Univ Fac Engn Dept Comp Engn Tarsus Turkey

Purpose This study aims to evolve an enhanced butterfly optimization algorithm (BOA) with respect to convergence and accuracy performance for numerous benchmark functions, rigorous constrained engineering design problems and an inverse synthetic aperture radar (ISAR) image motion compensation. Design/methodology/approach Adaptive BOA (ABOA) is thus developed by incorporating spatial dispersal strategy to the global search and inserting the fittest solution to the local search, and hence its exploration and exploitation abilities are improved. Findings The accuracy and convergence performance of ABOA are well verified via exhaustive comparisons with BOA and its existing variants such as improved BOA (IBOA), modified BOA (MBOA) and BOA with Levy flight (BOAL) in terms of various precise metrics through 15 classical and 12 conference on evolutionary computation (CEC)-2017 benchmark functions. ABOA has outstanding accuracy and stability performance better than BOA, IBOA, MBOA and BOAL for most of the benchmarks. The design optimization performance of ABOA is also evaluated for three constrained engineering problems such as welded beam design, spring design and gear train design and the results are compared with those of BOA, MBOA and BOA with chaos. ABOA, therefore, optimizes engineering designs with the most optimal variables. Furthermore, a validation is performed through translational motion compensation (TMC) of the ISAR image for an aircraft, which includes blurriness. In TMC, the motion parameters such as velocity and acceleration of target are optimally predicted by the optimization algorithms. The TMC results are elaborately compared with BOA, IBOA, MBOA and BOAL between each other in view of images, motion parameter and numerical image measuring metrics. Originality/value The outperforming results reflect the optimization and design successes of ABOA which is enhanced by establishing better global and local search abilities over BOA and its existing variants.

关键词： Engineering design Butterfly optimization algorithm ISAR imaging enhanced algorithm Benchmark functions CEC functions Motion compensation

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An enhanced Collaborative Filtering algorithm Based on Time Weight

An Enhanced Collaborative Filtering Algorithm Based on Time ...

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1st International Symposium on Information Engineering and Electronic Commerce

作者： Yang Huai-Zhen Li Lei Guilin Univ Elect Technol Sch Management Guilin Peoples R China Guilin Univ Elect Technol Coll Informat Technol Guilin Peoples R China

ISBN: (纸本)9780769536866

Because traditional collaborative filtering algorithm does not consider the influence of time on user's interests, taking equal consideration with different user's interests in different time leads to the neighbors may not be the similar neighbors set. For solving the problem, the enhanced algorithm endows each score with a time weight which declines gradually as time going, and uses the weighted score to search the nearest neighbors. Experiments of Movielens dataset show that the enhanced algorithm added time weight improves quality of recommendation system.

关键词： time weight collaborative filtering enhanced algorithm

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A multi-model evaluation of enhanced Tunicate Swarm Optimization for parameter identification

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ENERGY REPORTS 2024年 12卷 2049-2061页

作者： Singla, Manish Kumar Gupta, Jyoti Kumar, Ramesh Safaraliev, Murodbek Alsharif, Mohammed H. Aly, Ayman A. Kim, Mun-Kyeom Chitkara Univ Inst Engn & Technol Dept Interdisciplinary Courses Engn Rajpura Punjab India Jadara Univ Res Ctr Irbid Jordan KR Mangalam Univ Sch Engn & Technol Gurgaon 122003 Haryana India Ural Fed Univ Dept Automated Elect Syst Ekaterinburg 620002 Russia Sejong Univ Coll Elect & Informat Engn Dept Elect Engn 209 Neungdong Ro Seoul 05006 South Korea Taif Univ Coll Engn Dept Mech Engn Taif 21944 Saudi Arabia Chung Ang Univ Sch Energy Syst Engn 84 Heukseok Ro Seoul 06974 South Korea

Parameter identification for a proton exchange membrane fuel cell (PEMFC) entails employing optimisation techniques to discover the best unknown parameter values required to generate an accurate fuel cell performance prediction model. This technique, known as parameter identification, is important since manufacturers' data- sheets do not usually disclose these values. To address this, the manuscript examines five optimisation strategies, including the suggested algorithm, enhanced Tunicate Swarm Optimizer (ETSO), for predicting these parameters in PEMFCs. Each technique uses the six unknown parameters as decision variables, aiming to reduce the sum squared error (SSE) between anticipated and observed cell voltages. The data reveal that the suggested strategy outperforms existing approaches and cutting-edge optimizers. The two models are used to assess the dependability and performance of the PEMFC. The results are also compared to the non-parametric tests, and it is found that the suggested method outperforms the other algorithms in both suggested models.

关键词： Proton Exchange Membrane Fuel Cell Optimization enhanced algorithm Sum of Square Error Benchmark Test Function Non-Parametric Test

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Search space decomposition for resource-constrained project scheduling

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AUTOMATION IN CONSTRUCTION 2022年第0期134卷 104040-104040页

作者： Liu, Zhenyuan Hua, Zhengming Yang, Liu Deng, Raoyi Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Key Lab Educ Minist Image Proc & Intelligent Cont Wuhan 430074 Peoples R China

The mechanism with search space decomposition has been ever proposed for resource-constrained project scheduling which can reduce the search space. Theoretical equivalence for search spaces before and after decomposition is proven in this paper. It is shown that the mechanism can be easily incorporated in diverse algorithms. Four experiential strategies and a theoretical strategy are presented. The decomposition-based approach is nested in three classic algorithms to verify the effectiveness of the mechanism in numerical experiments. The results show that the decomposition-based approach can improve the quality of schedules under certain conditions, and the influence is diverse from the algorithms in which they are incorporated. Moreover, the most suitable decomposition strategies for each algorithm are different. Future work, such as priority-rules based on the decomposition strategies, strategies according to the parameters of activity network, and parallel computing with the decomposition mechanism, may bring new opportunities in project scheduling.

关键词： Resource-constrained project scheduling problem Search space decomposition Experiential decomposition strategy Theoretical decomposition strategy enhanced algorithm

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