Article
Computer Science, Artificial Intelligence
Tao Wang, Zhaoyao Shi, Bo Yu
Summary: This study introduces an accurate and robust method for fitting noisy and occlusion elliptic data using Levenberg-Marquardt iterations (LMIs) to minimize geometric distance, along with orthogonal angle segmentation for geometric error distance mapping, and dimension reduction by LMIs to avoid misconvergence and expensive computations. The method, based on two recent representative algorithms, is validated through simulation and real-world experiments, demonstrating its potential applications in various fields such as quality monitoring, three-dimensional reconstruction, and instrument calibration.
PATTERN RECOGNITION
(2021)
Article
Mathematics
Tzitlali Gasca-Ortiz, Francisco J. Dominguez-Mota, Diego A. Pantoja
Summary: This study determined optimal diffusion coefficients for Lake Zirahuen, Mexico, by analyzing images taken with a drone of a dye release experiment. Using a simple technique, the research showed the consequences of parameter estimation under particular conditions for this study site.
Article
Remote Sensing
Peng Zhang, Ruizhi Chen, Weiguo Dong, You Li, Yan Xu, Jian Kuang, Yuan Zhuang, Rong Yu, Mingyue Dong, Xiaoji Niu
Summary: This paper proposes two methods to enhance the robustness of capsule-endoscope positioning by initializing the capsule attitude using inertial measurements before estimating the position, and presenting an improved LM-based positioning algorithm based on vest-type magnetic sensor arrays.
GEO-SPATIAL INFORMATION SCIENCE
(2022)
Article
Chemistry, Multidisciplinary
Romuald Rzadkowski, Pawel Troka, Jerzy Manerowski, Leszek Kubitz, Miroslaw Kowalski
Summary: This paper presents an analysis of nonsynchronous rotor blade vibrations in the last stage of an LP steam turbine at various condenser pressures. The study found that the rotor blades vibrate simultaneously with two modes in non-nominal conditions, and the rotor frequencies remain unchanged. Additionally, flutter does not occur in the last stage for the tested condenser pressures and powers.
APPLIED SCIENCES-BASEL
(2022)
Article
Operations Research & Management Science
Natasa Krejic, Greta Malaspina, Lense Swaenen
Summary: This article proposes a decoupling procedure that splits large-scale nonlinear least squares problems into a sequence of smaller independent problems, and analyzes this method. The smaller problems are modified to compensate for disregarded dependencies. The method, a modification of the Levenberg-Marquardt method, has lower computational costs. Global convergence and local linear convergence are proven under suitable sparsity assumptions. The method is tested on network localization simulated problems with up to one million variables, demonstrating its efficiency.
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
(2023)
Article
Multidisciplinary Sciences
Jinyao Zhao, Xuejuan Zhang, Jinling Zhao
Summary: This paper proposes a tensor approximation algorithm based on the Levenberg-Marquardt method. It can decompose large-scale tensors into the sum of products of vector groups or obtain a low-rank tensor approximation without losing much accuracy. The algorithm introduces an Armijo-like rule for inexact line search. The adjustable result of tensor decomposition allows customization according to user requirements. Convergence is proven and numerical experiments show advantages over the classical method. It is applicable to both symmetric and asymmetric tensors and is expected to be useful for large-scale data compression and tensor approximation.
Article
Operations Research & Management Science
E. V. Castelani, R. Lopes, W. V. I. Shirabayashi, F. N. C. Sobral
Summary: This paper presents a low order-value optimization (LOVO) version of the Levenberg-Marquardt algorithm, which is well suited to deal with outliers in fitting problems. Numerical results demonstrate that the algorithm successfully detects and ignores outliers without too many specific parameters, and can be executed on large datasets. Comparisons with publicly available robust algorithms show that the present approach finds better adjustments in well known statistical models.
JOURNAL OF GLOBAL OPTIMIZATION
(2021)
Article
Computer Science, Artificial Intelligence
Adolfo Perrusquia
Summary: This paper proposes a complementary learning scheme for experience transference of unknown continuous time linear systems, inspired by the learning properties of hippocampus and neocortex via the striatum. The model involves optimizing controller data for the hippocampus and implementing a Q reinforcement learning algorithm for the neocortex, with an inverse reinforcement learning algorithm for complementary learning. Convergence of the proposed approach is analyzed using Lyapunov recursions, and simulations are carried out to verify its effectiveness.
Article
Thermodynamics
Cheng-Hung Huang, Li Chen
Summary: The study focuses on optimizing the design of a Y-shaped heat sink to reduce base plate temperature and enhance cooling performance. Experimental results show that in the optimized design, the fin stem height and branching angle are shorter and larger, respectively, than those of the original design, leading to improved heat dissipation performance.
CASE STUDIES IN THERMAL ENGINEERING
(2021)
Article
Mathematics, Applied
Maolin Liang, Bing Zheng, Yutao Zheng, Ruijuan Zhao
Summary: This paper introduces a new iterative method for solving multilinear systems based on unstructured tensor A in tensor-train format, utilizing an accelerated version of the LM method. The algorithm shows cubic convergence under local error bound condition and is not affected by the curse-of-dimensionality in terms of computational complexity. Numerical examples demonstrate the promising performance of the proposed method.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2021)
Article
Engineering, Multidisciplinary
Weiyi Shao, Jinyan Fan
Summary: This paper presents a stochastic Levenberg-Marquardt algorithm for nonlinear least squares problems and studies the global complexity of the algorithm. It derives an upper bound for the expected number of iterations to obtain an approximate solution where the gradient norm of the objective function is less than a given tolerance epsilon, which is O(epsilon-2).
JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION
(2023)
Article
Chemistry, Multidisciplinary
Hassan Saghi, Josko Parunov, Antonio Mikulic
Summary: This study analyzes the resistance of the bare hull of a tourist submarine with spherical heads moving in forward and transverse directions using Computational Fluid Dynamics in OpenFOAM. An Artificial Neural Network is trained to predict the resistance coefficients for different length-to-diameter ratios and Reynolds numbers, providing equations for the initial design of this type of submarines. Comparative analysis of prediction models is conducted, and practical application guidelines are provided.
APPLIED SCIENCES-BASEL
(2022)
Article
Operations Research & Management Science
Naoki Marumo, Takayuki Okuno, Akiko Takeda
Summary: This paper introduces a new Levenberg-Marquardt (LM) method for solving nonlinear least squares problems with convex constraints. The method proposes a new rule for updating the damping parameter to achieve global and local convergence even under the presence of convex constraints. The method solves a sequence of subproblems approximately using an (accelerated) projected gradient method.
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
(2023)
Article
Automation & Control Systems
Soumaya Marzougui, Asma Atitallah, Saida Bedoui, Kamel Abderrahim
Summary: This paper addresses the difficulty of identifying parameters for a fractional-order Hammerstein system with white noise by developing an algorithm and studying the convergence of the identified parameters. The proposed algorithm's performance is tested through two numerical examples.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2021)
Article
Automation & Control Systems
Yiming Zhong, Caoyang Yu, Rui Wang, Tianqi Pei, Lian Lian
Summary: In this paper, an adaptive anti-noise least squares algorithm (ANLS) is proposed for parameter identification of an unmanned marine vehicle in the presence of measurement noise. The algorithm establishes a nonlinear model and adds a noise reduction term to balance anti-noise effect and identification accuracy. The simulation and experimental results demonstrate the excellent anti-noise and maneuvering prediction abilities of the ANLS algorithm.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Yingkang Xie, Qian Ma, Jason Gu, Guopeng Zhou
Summary: This article addresses the problem of adaptive fuzzy event-triggered fixed-time practical tracking control for flexible-joint robot system. Fuzzy logic systems are used due to the difficulties in obtaining the system's nonlinearities. Second-order command filters and a novel compensation system are employed to ensure stability and convergence of the error. The proposed control strategy, based on backstepping technique, guarantees boundedness of the closed-loop system variables and arbitrary small tracking error in fixed time.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Mathematics, Applied
Sayooj Aby Jose, Raja Ramachandran, Dumitru Baleanu, Hasan S. Panigoro, Jehad Alzabut, Valentina E. Balas
Summary: This paper presents a mathematical model for dynamic systems of substance addiction using the ABC fractional derivative. The stability of the equilibrium points and the basic reproduction number are investigated. The theoretical results of solution existence and uniqueness for the proposed model are verified using fixed point theory and nonlinear analytic techniques. A numerical technique is established to obtain the approximate solution of the model, and numerical graphs corresponding to different fractional orders are provided. Furthermore, a numerical simulation is conducted to study the transmission of substance addiction in scenarios with different basic reproduction numbers.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2023)
Article
Engineering, Mechanical
Sayooj Aby Jose, R. Raja, B. Omede, Ravi P. Agarwal, J. Alzabut, J. Cao, V. E. Balas
Summary: In this paper, a deterministic mathematical model for the transmission dynamics of co-infection of Dengue Fever and Zika virus is formulated and analyzed. It is found that each disease undergoes backward bifurcation when the reproduction number of the sub-models is less than one. Simulation of the full model provides a clear visualization of disease transmission, and the numerical solution of the model is provided in detail.
NONLINEAR DYNAMICS
(2023)
Article
Green & Sustainable Science & Technology
Muhammad Ahmad Iqbal, Muhammad Salman Fakhar, Noor Ul Ain, Ahsen Tahir, Irfan Ahmad Khan, Ghulam Abbas, Syed Abdul Rahman Kashif
Summary: This study proposes a novel deterministic thermal economic dispatch method with the improved Accelerated Particle Swarm Optimization (APSO) algorithm to reduce the time complexity for the CSTHTS optimization problem. The results outperform many state-of-the-art algorithms applied in the literature, and the statistical tests have established the superiority of the improved APSO algorithm over other metaheuristic algorithms in solving the chosen test case of the CSTHTS problem.
Article
Green & Sustainable Science & Technology
Raheel Muzzammel, Rabia Arshad, Ali Raza, Nebras Sobahi, Umar Alqasemi
Summary: Transmission lines are crucial for power systems and their security is vital. A method for fault analysis and classification in three-phase transmission lines is proposed, with high accuracy and efficiency. Faults can be located and classified using power measurements and voltage profiles. Simulations show an accuracy of over 97% and minimal time difference between actual and estimated faults. This technique ensures effective and rapid protection against faults.
Article
Computer Science, Artificial Intelligence
Tanusree Podder, Diptendu Bhattacharya, Priyanka Majumder, Valentina Emilia Balas
Summary: Automatic facial expression recognition plays a crucial role in various human-computer based applications. Traditional handcrafted methods often fail to produce superior results in real-world environments. A deep learning-based approach with minimal parameters is proposed, which achieves better results for both lab-controlled and wild datasets.
PEERJ COMPUTER SCIENCE
(2023)
Article
Green & Sustainable Science & Technology
Ghulam Abbas, Irfan Ahmad Khan, Naveed Ashraf, Muhammad Taskeen Raza, Muhammad Rashad, Raheel Muzzammel
Summary: In recent years, different metaheuristic techniques have been widely used to solve economic load dispatch problems. However, the randomization involved in these techniques requires extensive runs to obtain an optimal solution, which can be laborious and time-consuming. On the other hand, deterministic optimization algorithms based on advanced calculus techniques provide consistent solutions on each run, making them suitable for solving constrained optimization problems like economic load dispatch. The experiments on various thermal test systems confirm that the constrained optimization algorithm can achieve comparable results to metaheuristic techniques in terms of total fuel cost, especially for less-constrained problems, while significantly reducing computation time.
Article
Chemistry, Multidisciplinary
Sajjad Hussain, Muhammad Humza, Tanveer Yazdan, Ghulam Abbas, Han-Wook Cho
Summary: Hydro generation is a century-old, simple and cost-effective method of electricity generation. However, the use of a pump as a turbine (PAT) in low-head and small-scale hydro plants has limitations due to its inability to respond to variable flows. In this study, a simple and economical technique using water columns connected in parallel (PWCs) was proposed to smooth the output of a PAT on variable/decreasing water flow profiles. The PWC technique maintained the flow at the inlet of the turbine, resulting in a smooth output even at minimum water flow/head conditions.
APPLIED SCIENCES-BASEL
(2023)
Editorial Material
Engineering, Chemical
Dipankar Deb, Valentina Emilia Balas, Mrinal Kaushik
Article
Computer Science, Cybernetics
Fiseha B. Tesema, Jason Gu, Wei Song, Hong Wu, Shiqiang Zhu, Zheyuan Lin, Min Huang, Wen Wang, Rajesh Kumar
IEEE SYSTEMS MAN AND CYBERNETICS MAGAZINE
(2023)
Article
Automation & Control Systems
Deguang Xu, Hao Chen, Xing Wang, Vitor Pires, Joao Martins, Alecksey Anuchin, Xiaodong Li, Ryszard Palka, Jason Gu
Summary: Differential power processing (DPP) is a highly competitive architecture for photovoltaic (PV) applications due to its high energy efficiency and mitigation of mismatch issues. However, the complexity of coupling between DPP converters poses challenges in terms of maximum power point tracking (MPPT) in DPP-based PV systems. This article presents a method that makes the application of synchronous MPPT in DPP topology feasible based on a simple and easy partial decoupling method, improving the efficiency of MPPT and scalability of the system.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Computer Science, Information Systems
Muhammad Anas Baig, Syed Abdul Rahman Kashif, Irfan Ahmad Khan, Ghulam Abbas
Summary: This paper presents a new approach to Direct Model Predictive Control (DMPC) for multilevel inverters, aiming to achieve perfect inverter current control without exhaustive search. The proposed method can be applied to any multilevel inverter, reducing the computational burden.
Article
Computer Science, Information Systems
Fiseha B. Tesema, Jason Gu, Wei Song, Hong Wu, Shiqiang Zhu, Zheyuan Lin
Summary: Active speaker detection (ASD) is about identifying the person speaking in a video among visible human instances. This study proposes an efficient audiovisual fusion (AVF) approach that captures correlations between facial regions and sound signals, focusing on discriminative facial features and associating them with corresponding audio features, resulting in improved detection accuracy.
Article
Automation & Control Systems
Rong Liu, Jiaxing Wang, Yaru Chen, Yin Liu, Yongxuan Wang, Jason Gu
Summary: This paper proposes a neuromuscular control method called TMS-PPO, which is based on time-varying muscle synergy (TMS) and proximal policy optimization (PPO). The method decomposes electromyogram (EMG) activation signals to obtain TMSs, and trains network weights to generate scale and phase coefficients through PPO. The coefficients modulate the TMSs to generate appropriate activation patterns for motion learning of the musculoskeletal system.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
Sanjiban Sekhar Roy, Ching-Hsien Hsu, Akash Samaran, Ranjan Goyal, Arindam Pande, Valentina E. Balas
Summary: Coronary artery disease (CAD) is a significant cause of heart attack, especially among those 40 years old or younger. This research proposes an image segmentation approach using Convolution Neural Networks (CNN) for diagnosing CAD, aiming to achieve state-of-the-art results.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)