Combining an improved political optimizer with convolutional neural networks for accurate anterior cruciate ligament tear detection in sports injuries DOI Creative Commons
Wei Hu, Saeid Razmjooy

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Фев. 26, 2025

A new technique has been developed to identify ACL tears in sports injuries. This method utilizes a Convolutional Neural Network (CNN) combination with modified Political Optimizer (IPO) algorithm, resulting major breakthrough detecting tears. The study provides an innovative approach this type of injury. CNN/IPO surpasses traditional optimization techniques, ensuring precise and timely detection the potential significantly improve treatment results, enabling clinicians intervene promptly effectively, leading enhanced recovery rehabilitation for athletes. integration CNN IPO algorithm unparalleled level accuracy efficiency identifying tears, facilitating more tailored strategies sports-related findings have revolutionize way medical professionals musculoskeletal injuries, enhancing overall well-being athletic performance. research's significance extends beyond medicine, illuminating avenues management paving advancements injury diagnosis treatment.

Язык: Английский

Application of modified seagull optimization algorithm with archives in urban water distribution networks: Dealing with the consequences of sudden pollution load DOI Creative Commons
Qichun Wang, Mingxiang Zhang,

Sama Abdolhosseinzadeh

и другие.

Heliyon, Год журнала: 2024, Номер 10(3), С. e24920 - e24920

Опубликована: Янв. 22, 2024

This study focuses on the optimization of consequence management actions in urban water distribution network. The EPANET simulation model is employed combination with multi-objective modified seagull algorithm (MOMSOA) based archives for a more efficient process. Two objective functions are developed: minimizing reactive activities (cost reduction) and consumed pollution mass. utilization shut-off valves hydrants isolating network discharging explored. Without management, 84.5 kg consumed. With 18 activities, consumption was reduced to 59.8 kg. Also, compare proposed method other algorithms, interaction curve between amount pollutant mass obtained using methods, including MOSOA, NSGA-II, MOPSO, MOSMA. According curve, performed better reducing pollution. Extracting optimal MOMSOA maximum takes about 80 min. archive technique significantly shortens this time real-time management. approach demonstrates that increasing population decreases extraction curves objectives by up 60 %. A small capacity slightly increases required extract due searching similar solutions. However, utilizing enables

Язык: Английский

Процитировано

4
Modified artificial neural network based on developed snake optimization algorithm for short-term price prediction DOI Creative Commons

Baozhu Li,

Majid Khayatnezhad

Heliyon, Год журнала: 2024, Номер 10(5), С. e26335 - e26335

Опубликована: Фев. 13, 2024

Short-term prices prediction is a crucial task for participants in the electricity market, as it enables them to optimize their bidding strategies and mitigate risks. However, price signal subject various factors, including supply, demand, weather conditions, renewable energy sources, resulting high volatility nonlinearity. In this study, novel approach introduced that combines Artificial Neural Networks (ANN) with newly developed Snake Optimization Algorithm (SOA) forecast short-term signals Nord Pool market. The snake optimization algorithm utilized both structure weights of neural network, well select relevant input data based on similarity curves wind production. To evaluate effectiveness proposed technique, experiments have been conducted using from two regions namely DK-1 SE-1, across different seasons time horizons. results demonstrate technique surpasses alternative methods Particle Swarm (PSO) Genetic Algorithms-based Network (PSOGANN) Gravitational Search Algorithm-based (GSONN), exhibiting superior accuracy minimal error rates prediction. show average MAPE index region 3.1292%, which 32.5% lower than PSOGA method 47.1% GSONN method. For SE-1 region, 2.7621%, 40.4% 64.7% Consequently, holds significant potential valuable tool market enhance decision-making planning activities.

Язык: Английский

Процитировано

4
Improving the Method of Short-term Forecasting of Electric Load in Distribution Networks using Wavelet transform combined with Ridgelet Neural Network Optimized by Self-adapted Kho-Kho Optimization Algorithm DOI Creative Commons
Yaoying Wang, Shudong Sun, Gholamreza Fathi

и другие.

Heliyon, Год журнала: 2024, Номер 10(7), С. e28381 - e28381

Опубликована: Март 26, 2024

This paper proposes a new method for short-term electric load forecasting using Ridgelet Neural Network (RNN) combined with wavelet transform and optimized by Self-Adapted (SA) Kho-Kho algorithm (SAKhoKho). The aim of this is to improve the accuracy reliability forecasting, which essential planning operation competitive electrical networks. proposed uses Wavelet Transform (WT) decompose data into different frequency components applies RNN each component separately. is, then, SAKhoKho algorithm, an improved version KhoKho that can adapt search parameters dynamically. trained tested on Zone Preliminary Billing Data from PJM regulatory area, updated every two weeks based Intercontinental Exchange (ICE) figures. compared six other cutting-edge methods literature, including SVM/SA, hybrid, ARIMA, MLP/PSO, CNN, RNN/KhoKho/WT. results show achieves lowest Mean Absolute Error (MAE) 7.7704 Root Square (RMSE) 17.4132 among all methods, indicating its superior performance. capture temporal dependencies in optimize RNN's weights minimize error function. promising technique as it provide accurate reliable predictions next hour previous 24 h data.

Язык: Английский

Процитировано

4
Optimization for energy-aware design of task scheduling in heterogeneous distributed systems: a meta-heuristic based approach DOI
Cen Li, Liping Chen

Computing, Год журнала: 2024, Номер 106(6), С. 2007 - 2031

Опубликована: Апрель 7, 2024

Язык: Английский

Процитировано

4
Day-ahead resilience-economic energy management and feeder reconfiguration of a CCHP-based microgrid, considering flexibility of supply DOI Creative Commons
Jaber Moosanezhad, Ali Basem,

Farshad Khalafian

и другие.

Heliyon, Год журнала: 2024, Номер 10(11), С. e31675 - e31675

Опубликована: Май 24, 2024

Many challenges have emerged due to the intense integration of renewables in distribution system and associated uncertainties power generation. Consequently, local management strategies are developed at level, leading emergence concepts such as microgrids. Microgrids include a variety heating, cooling, electrical resources loads, operators' aim is minimize operation outage costs. Since significant outages typically caused by events earthquakes, floods, hurricanes, microgrid operators compelled improve resilience ensure uninterrupted service during conditions. A mixed-integer linear programming model designed this paper optimize energy structural configuration This optimization aims enhance cost, minimizing capital costs well loss pollution. To achieve these goals, several tools implemented including reconfiguration, storages, combined heat units, wind turbines, photovoltaic panels, capacitors. Four case studies defined prove efficiency. The first study focuses on for cost minimization. second emphasizes improvement alongside management, aiming resilience. In third case, microgrid's reconfiguration capability also added case. Therefore, both within simultaneously operational Finally, fourth problem studied multi-objective approach. By comparing results, impact microgrids elucidated. considering concept based results 2, it found that operating increased an average 10.38%. However, because reducing 13.91%, total reduced 5.93 % 2 compared 1. Furthermore, when cases 3, effect can be determined. It observed decreased 4.5%. Moreover, 1.61%, resulting overall reduction objective function 2.43% 3 2.

Язык: Английский

Процитировано

4
Simulating runoff changes and evaluating under climate change using CMIP6 data and the optimal SWAT model: a case study DOI Creative Commons

Sai Wang,

Hongjin Zhang,

Tuan-Tuan Wang

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Окт. 5, 2024

This study examines the influence of climate change on hydrological processes, particularly runoff, and how it affects managing water resources ecosystem sustainability. It uses CMIP6 data to analyze changes in runoff patterns under different Shared Socioeconomic Pathways (SSP). also a Deep belief network (DBN) Modified Sparrow Search Optimizer (MSSO) enhance forecasting capabilities SWAT model. DBN can learn complex improve accuracy forecasting. The meta-heuristic algorithm optimizes models through iterative search processes finds optimal parameter configuration Optimal Model accurately predicts patterns, with high precision capturing variability, strong connection between projected actual data, minimal inaccuracy its predictions, as indicated by an ENS score 0.7152 R

Язык: Английский

Процитировано

4
The improved aquila optimization approach for cost-effective design of hybrid renewable energy systems DOI Creative Commons

Zhou Yin,

Zhimin Chen,

Ziwei Gong

и другие.

Heliyon, Год журнала: 2024, Номер 10(6), С. e27281 - e27281

Опубликована: Март 1, 2024

The growing demand for renewable energy systems is driven by climate change concerns, government support, technological advancements, economic viability, and security. These factors combine to create a strong momentum towards clean sustainable future. Governments, governments, individuals are increasingly aware of the environmental impacts traditional sources adopting solutions. Hybrid Renewable Energy Systems (HRES) developed as an effective way meeting demands in remote locations. complexity system components fluctuation make it difficult design economical HRES. In this study, Improved Aquila Optimization (IAO) approach has been suggested powerful tool optimize HRES design. study addresses implementation IAO emphasizes its advantages over other optimization techniques. Through extensive simulations analyses, our findings demonstrate superior performance algorithm improving efficiency cost-effectiveness process using resulted significant reduction overall costs, achieving estimated Net Present Cost (NPC) $201,973. It translates cost 25% compared conventional Furthermore, analysis reveals that enhances utilization sources, leading 15% increase generation efficiency. results highlight effectiveness addressing challenges associated with designing By significantly reducing costs efficiency, facilitates adoption areas. outcomes emphasize importance utilizing advanced techniques, such IAO, ensure viability sustainability

Язык: Английский

Процитировано

3
Microgrids Efficiency Improvement for National Electricity Network Leveraging Beluga Whale Optimization DOI Creative Commons

Dianzuo Li,

Wei Feng,

Mohammadreza Fathi

и другие.

Heliyon, Год журнала: 2024, Номер unknown, С. e30018 - e30018

Опубликована: Апрель 1, 2024

Managing of real-time energy in microgrids connected to grid is a relatively new technology that becoming increasingly popular the industry. It enables connect with each other and wider electrical increase efficiency improve resiliency while reducing costs emissions. also grid-connected dynamically adjust changing conditions, allowing for upgraded infrastructure improved security. However, identifying an accurate efficient approach management critical. In this regards, paper introduces modified metaheuristic, Boosted Beluga Whale Optimizer (BBWO), application optimize battery controlling CM (community microgrid). This amendment involves changes cost function so it better captures charging/discharging operations. A dynamic penalty then suggested sake further improves function. The effectiveness determined through case study, operational over 96h time horizon. From results, battery's cycles provides lower expenses $29.70 96-hour Further, proposed innovative encourages optimal charging from RESs utility could reduce objective significantly. was demonstrated constantly trying maintain full charge, which requires expenditure $33.14 electricity. still less than original cost, but allows high levels be maintained across all periods. Additionally, prevents any issues stemming low maximizes life battery. Overall, regularized BBWO algorithm, offered adapted needs society, suitable solution management.

Язык: Английский

Процитировано

3
A Novel State Machine-Fractional Order PID Control Strategy for Energy Management Framework to Optimize the Consumption from Fuel Cell in DC Microgrid DOI Creative Commons

Shashi Bhushan Mohanty,

Satyajit Mohanty

IEEE Access, Год журнала: 2024, Номер 12, С. 136160 - 136182

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

3
Optimizing electric load forecasting with support vector regression/LSTM optimized by flexible Gorilla troops algorithm and neural networks a case study DOI Creative Commons
Zhirong Zhang, Qiqi Zhang, Haitao Liang

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Сен. 27, 2024

Язык: Английский

Процитировано

3