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Enhancing Surgery Scheduling in Health Care Settings With Metaheuristic optimization models: Algorithm Validation Study

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JMIR MEDICAL INFORMATICS 2025年 13卷 e57231页

作者： Lopes, Joao Guimaraes, Tiago Duarte, Julio Santos, Manuel Univ Minho Algoritmi Res Ctr Rua Univ P-4800058 Braga Portugal

Background: Health care is facing many challenges. The recent pandemic has caused a global reflection on how clinical and organizational processes should be organized, which requires the optimization of decision-making among managers and health care professionals to deliver care that is increasingly patient-centered. The efficiency of surgical scheduling is particularly critical, as it affects waiting list management and is susceptible to suboptimal decisions due to its complexity and constraints. Objective: In this study, in collaboration with one of the leading hospitals in Portugal, Centro Hospitalar e Universit & aacute;rio de Santo Ant & oacute;nio (CHUdSA), a heuristic approach is proposed to optimize the management of the surgical center. Methods: CHUdSA's surgical scheduling process was analyzed over a specific period. By testing an optimization approach, the research team was able to prove the potential of artificial intelligence (AI)-based heuristic models in minimizing scheduling penalties-the financial costs incurred by procedures that were not scheduled on time. Results: The application of this approach demonstrated potential for significant improvements in scheduling efficiency. Notably, the implementation of the hill climbing (HC) and simulated annealing (SA) algorithms stood out in this implementation and minimized the scheduling penalty, scheduling 96.7% (415/429) and 84.4% (362/429) of surgeries, respectively. For the HC algorithm, the penalty score was 0 in the urology, obesity, and pediatric plastic surgery medical specialties. For the SA algorithm, the penalty score was 5100 in urology, 1240 in obesity, and 30 in pediatric plastic surgery. Together, this highlighted the ability of AI-heuristics to optimize the efficiency of this process and allowed for the scheduling of surgeries at closer dates compared to the manual method used by hospital professionals. Conclusions: Integrating these solutions into the surgical scheduling process increases ef

关键词： health care surgery scheduling problem metaheuristic model model optimization surgery scheduling artificial intelligence

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Apply BERT optimization algorithm to improve the accuracy of speech recognition for non-native English learners

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JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2025年第1期25卷 944-962页

作者： Tao, Zhenli Wuhan Univ Bioengn Sch Foreign Languages 1 Hanshi Rd Wuhan 420010 Hubei Peoples R China

The voice recognition of non-native tongue English learners is an important challenge in the field of speech recognition. Existing technology still has obvious defects when dealing with non-native tongue pronunciation. This study combined BERT (Bidirectional Encoder Representations from Transformers) and CNN-HMM models and introduced an attention mechanism to improve the accuracy of voice recognition of non-native tongue English learners. It used the pre-trained BERT model to extract the context of the voice signal and used the CNN (Convolutional Neural Network) for local feature extraction, and used the Hidden Markov model (HMM) to make a sequence model building model to capture ability of key features. The experimental results show that the accuracy rate of voice recognition of the BERT-CNN-HMM model in this article reaches 88.9% under normal speed, which is significantly better than 78.5% of the traditional HMM model. Under different noise levels, the accuracy of the article's model in low noise, medium noise, and high noise environments is 86.9%, 80.5%, and 72.8%, respectively, which are higher than other comparative models. The accuracy of the models in this article remained above 83.8% when processing different accents, showing strong adaptation to strong adaptation and generality. It can be seen from the experimental results that the model of this article can significantly improve the accuracy of the voice recognition of non-native English learners and provide a new direction for further research in the field of voice recognition.

关键词： BERT optimization algorithm convolutional neural network-hidden Markov model speech recognition non-native learners attention mechanism feature extraction model optimization

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Customization and optimization of SSD-based Neural Network model for Detection of External Force Damage on Transmission Lines 4

Customization and Optimization of SSD-based Neural Network M...

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4th International Workshop on Pattern Recognition (IWPR)

作者： Chi, Yingying Liu, Rui Cui, Wenpeng Zhang, Haifeng Yuan, Yidong Beijing Smart Chip Microelect Technol Co Ltd State Grid Key Lab Power Ind Chip Design & Anal T Beijing 100192 Peoples R China

ISBN: (数字)9781510631144

ISBN: (纸本)9781510631144

Based on the principle of SSD (Single Shot Multibox Detector) convolutional neural network algorithm, this paper develops corresponding training strategies, and uses the source data generated under a large number of power-grid scenarios to train and generate a 100-megabyte neural network model for intelligent monitoring of external force damage on transmission lines. Using the deep compression technology, the trained neural network model is re-trained and optimized in a targeted manner to ensure a compression ratio of 30%-50% under the premise that the accuracy is not degraded. In this way, the hardware storage resource configuration is more reasonable when the model is deployed on the embedded platform.

关键词： SSD convolutional neural network deep compression model optimization intelligent monitoring

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Analysis and optimization of Equivalent Magnetic Circuit model for a Hybrid Axial Field Flux-Switching Permanent Magnet Machine 21

Analysis and Optimization of Equivalent Magnetic Circuit Mod...

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21st International Conference on Electrical Machines and Systems (ICEMS)

作者： Zhu, Lian-li Xu, Da Li, Qiang Sun, Wei Hu, Ya-qian Nanjing Univ Sci & Technol Sch Automat Nanjing Jiangsu Peoples R China

ISBN: (纸本)9788986510201

The hybrid axial field flux-switching permanent magnet machine (HAFFSPMM) is a novel hybrid excitation machine with the advantages of symmetric back-EMF waveform and high torque density. In this paper, the original nonlinear equivalent magnetic circuit (EMC) model of the HAFFSPMM is established, which exhibits that the no-load flux linkage and back-EMF calculated by the original model agree well with the results obtained through finite element method (FEM). Considering the end leakage of the permanent magnets (PMs), the EMC model is optimized The analysis result shows that the optimized results coincide better with the FEM calculations. The flux regulation capability is analyzed by the optimized model, which further verifies the accuracy of the EMC model.

关键词： axial field finite element method equivalent magnetic circuit model optimization

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A Further Improved Support Vector Machine model Along with Particle Swarm optimization for Face Orientations Recognition Based on Eigeneyes by Using Hybrid Kernel

A Further Improved Support Vector Machine Model Along with P...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEE IEEM)

作者： Liu, Y. Shi, Y. K. Xu, M. W. Zhang, L. L. Yu, N. Ding, Y. L. Shandong Univ Sci & Technol Dept Ind Engn Qingdao Peoples R China Xi An Jiao Tong Univ Coll Management Xian Shaanxi Peoples R China State Key Lab Breeding Base Mine Disaster Prevent Qingdao Peoples R China Shandong Univ Sci & Technol Dept Int Econ & Trade Qingdao Peoples R China

ISBN: (纸本)9781538609484

The learning vector quantization (LVQ), back propagation neural network (BPNN), and support vector machine (SVM) models were established to recognize face orientations. A precision function (P) was proposed to compute each model's precision with confusion matrix. The aforehand models were improved by intelligent algorithms to become LVQ with K-fold cross validation (CV-LVQ) model, BPNN with GA (GA-BPNN) model, and SVM with particle swarm optimization (PSO-SVM) model. The kernel function in the PSO-SVM model was assumed to RBF kernel which had relatively weaker learning ability. Hence the PSO-SVM model was further improved with a hybrid kernel that was fused with the generalization performance of global kernel and the learning ability of local kernel. The further improved PSO-SVM (IPSO-SVM) model possessed a 1.63 to 9.25 percent higher precision than PSO-SVM model. There were no obvious differences in the average elapsed time (AET) between IPSO-SVM model and PSO-SVM model. The results show that IPSO-SVM model not only reaches an outstanding precision of 98.14%, but also was practicable for the recognition of face orientations.

关键词： Eigeneyes face orientations recognition hybrid kernel model optimization precision function

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optimization and Application of the Transport Cost model under the Transfer Supply System in Logistics Enterprises 8

Optimization and Application of the Transport Cost Model und...

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8th International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)

作者： Rong, Pu Lijiang Teachers Coll Sch Int Tourism & Business Management Lijiang 674199 Peoples R China

ISBN: (数字)9781538682463

ISBN: (纸本)9781538682463

High transport cost has always been a major problem faced by Chinese logistics enterprises. Based on the actual cargo transport of logistics enterprises and under the premise of the scientific hypothesis, related contents of the mathematical model are used and transport costs are taken into an important factor affecting the operation of enterprises. Based on related data of a certain logistics service company and with the mathematical model;the company's transport routes are re-planned to achieve efficient and standardized logistics transport.

关键词： transfer supply system model optimization rationalization oftransport costs

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Some Thoughts on model-Based Test optimization 19

Some Thoughts on Model-Based Test Optimization

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19th IEEE International Conference on Software Quality, Reliability and Security (QRS)

作者： Liu, Pan Li, Yudong Li, Zhaojun (Steven) Shanghai Business Sch Shanghai Peoples R China Engn Res Ctr Software Testing & Evaluat Fujian Pr Fuzhou Peoples R China Western New England Univ Dept Ind Engn & Engn Management Springfield MA USA

ISBN: (纸本)9781728139258

As a test method, model-based testing has been proven to have the ability to find inconsistencies between a software system and its design model and objectives. Because the design of the model is independent of the development of program codes, the generation of test cases from the model is synchronized with the development of software codes, saving the software test cost. This paper reviews the development of model-based test methods from the optimization perspective and presents five issues in the test optimization process. In addition, the paper discusses four types of optimization strategies for reducing the redundancy of test sequences and an optimization method by using the regular expression model. Finally, this paper gives two potential research directions, including model optimization and software bug location in the program, for model-based testing in the future. This research contributes to the applications of model-based testing in industry.

关键词： test optimization model-based testing redundancy reduction model optimization

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An elevator scheduling optimization model considering the probability of taking the elevator based on Monte Carlo Algorithm 5

An elevator scheduling optimization model considering the pr...

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IEEE 5th Information Technology and Mechatronics Engineering Conference (ITOEC)

作者： Zhang, Yufeng Zhao, Han Huang, Shijie Guo, Fengyu Harbin Inst Technol Sch Astronaut Harbin Peoples R China

ISBN: (数字)9781728143231

ISBN: (纸本)9781728143231;9781728143224

In view of the different probability of residents of different floors in high-rise buildings taking the elevator during the peak period of a day, this paper proposes an optimization scheduling model based on Monte Carlo Algorithm, making the existing model more accurate. The automatic counting module (ACM) based on infrared sensor is used to measure and record the number of passengers on different floors. On the basis of a large amount of data obtained from the research, the probability of taking the elevator is calculated, and the cubic polynomial fitting curve is generated based on the least square method, which is applied to the implementation of Monte Carlo Algorithm, and an optimized elevator scheduling model is obtained. At the same time, the optimized model and the existing model are compared in different aspects to generate visual comparison result. In the hypothesis of this paper, under the condition that the number of floors is 20 and the number of households on each floor is 50, the existing model will have a relative error of 10%-20%, and the number of passengers transported by the elevator below 10 floors will be significantly reduced with a relative error of more than 10%. At last, from the elevator scheduling model, a "one-to-many" model can be abstracted. We find that the model optimization idea used in this problem has certain guiding significance in dealing with some other practical problems.

关键词： Automatic counting module based on infrared sensor probability of taking the elevator(PTE) Monte Carlo Algorithm least square method data research model optimization one-to-many model

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Research on optimization model of Taxi-carpooling Expenses

Research on Optimization Model of Taxi-carpooling Expenses

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2nd International Conference on Civil Engineering, Architecture and Building Materials (CEABM 2012)

作者： He, Feng Qiu, Xin Yang, Qing Chen, Jiongdi Yu, Haiqi Zhejiang Normal Univ Coll Engn Jinhua 321004 Peoples R China

ISBN: (纸本)9783037854242

In order to solve cost-sharing problems for taxi-carpooling passengers, the optimization model of sharing taxi-carpooling expenses was established taking both taxi-driver and passengers' benefits into fully consideration. Based on the fact that passengers would pay for their own share in proportion, the optimization model was made with the objective function aiming at minimum consumption of time and money. In view of its features, the theoretical model was further developed comparing expenses in theory with that under existing conditions. The results show that this optimization model of sharing taxi-carpooling expenses can meet the need of both passengers and taxi driver. Moreover, the research findings will provide a firm technical support and guarantee for a satisfactory solution to cost-sharing problems on taxi-carpooling.

关键词： Taxi-carpool Cost-sharing model optimization

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The Research and optimization of Hybrid System MLD model Parameters Based on HYSDEL 27

The Research and Optimization of Hybrid System MLD Model Par...

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27th Chinese Control and Decision Conference (CCDC)

作者： Sheng, Xuelai Wang, Yu-Hong China Univ Petr East China Coll Informat & Control Engn Qingdao 2665S0 Peoples R China

ISBN: (纸本)9781479970162

The MLD model can be created by HYSDEL toolbox automatically. It provides great convenience for the MLD research. But the number o Ibinary variables, auxiliary continuous variables and inequality constraints in the MLD model cannot satisfy our requirements. In this paper, we proposed three steps optimization to optimize the model parameters. It can effectively reduce the amount of binary variables, auxiliary continuous variables and inequality constraints in that MLD model established by HYSDEL. The proposed algorithm was illustrated in saturation characteristic function and promising results were achieved.

关键词： MLD HYSDEL Saturation Characteristic model optimization

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