Short-Term Photovoltaic Power Forecasting Based on the VMD-IDBO-DHKELM Model by Shengli Wang, Xiaolong Guo, Tianle Sun, Lihui Xu, Jinfeng Zhu, Zhicai Li, Jinjiang Zhang

“…A short-term photovoltaic power forecasting method is proposed, integrating variational mode decomposition (VMD), an improved dung beetle algorithm (IDBO), and a deep hybrid kernel extreme learning machine (DHKELM). …”
Get full text

RTRS algorithm in low-power Internet of things by Yuchen CHEN, Yuan CAO, Laipeng ZHANG, Lianghui DING, Feng YANG

“…Considering the feature of periodical uplink data transmission in IEEE 802.11ah low-power wide area network (LWPAN),a real-time RAW setting (RTRS) algorithm was proposed.Multiple node send data to an access point (AP),and the uplink channel resources were divided into Beacon periods in time.During a Beacon period,AP firstly predicted the next data uploading time and the total amount of devices that will upload data in the next Beacon period.The AP calculated the optimal RAW parameters for minimum energy cost and broadcasted the information to all node.Then all devices upload data according to the RAW scheduling.The simulation results show that the current network state can be predicted accurately according to the upload time of the terminal in the last period.According to the predicted state,raw configuration parameters can be dynamically adjusted and the energy efficiency can be significantly improved.…”
Get full text

RTRS algorithm in low-power Internet of things by Yuchen CHEN, Yuan CAO, Laipeng ZHANG, Lianghui DING, Feng YANG

“…Considering the feature of periodical uplink data transmission in IEEE 802.11ah low-power wide area network (LWPAN),a real-time RAW setting (RTRS) algorithm was proposed.Multiple node send data to an access point (AP),and the uplink channel resources were divided into Beacon periods in time.During a Beacon period,AP firstly predicted the next data uploading time and the total amount of devices that will upload data in the next Beacon period.The AP calculated the optimal RAW parameters for minimum energy cost and broadcasted the information to all node.Then all devices upload data according to the RAW scheduling.The simulation results show that the current network state can be predicted accurately according to the upload time of the terminal in the last period.According to the predicted state,raw configuration parameters can be dynamically adjusted and the energy efficiency can be significantly improved.…”
Get full text

Cooperative Downloading in Mobile Ad Hoc Networks: A Cost-Energy Perspective by He Li, Yang Yang, Xuesong Qiu, Zhipeng Gao, Guizhen Ma

“…This paper proposes a cost distribution (OCD) algorithm and a content distribution algorithm based on auction (OCDA) for mobile ad hoc networks based on relative location of nodes and local optimization theory. …”
Get full text

An Inter-Regional Lateral Transshipment Model to Massive Relief Supplies with Deprivation Costs by Shuanglin Li, Na Zhang, Jin Qin

“…Specifically, JADE is employed in the first stage to allocate the volume of massive relief supplies, aiming to minimize deprivation costs, while IALNS optimizes intermodal routing in the second stage to minimize the weighted sum of transportation time and cost. …”
Get full text

Book Recommendation Using Collaborative Filtering Algorithm by Esmael Ahmed, Adane Letta

“…Moreover, using hyperparameter tuning with SVD also has an improvement on model performance compared with the existing SVD algorithm.…”
Get full text

An Underwater Localization Algorithm Based on the Internet of Vessels by Ziqi Wang, Ying Guo, Fei Li, Yuhang Chen, Jiyan Wei

“…The algorithm is composed of three stages: crowdsensing, denoising, and aggregation-based optimization. …”
Get full text

Neural network-based link prediction algorithm by Yonghao PAN, Hongtao YU, Shuxin LIU

Get full text

Stochastic Explicit Calibration Algorithm for Survival Models by Jeongho Park, Sangwook Kang, Gwangsu Kim

“…In addition, we highlight how improved calibration can improve downstream tasks, including optimizing resource allocation and improving patient care decisions. …”
Get full text

A Novel Framework for Improving Soil Organic Carbon Mapping Accuracy by Mining Temporal Features of Time-Series Sentinel-1 Data by Zhibo Cui, Bifeng Hu, Songchao Chen, Nan Wang, Defang Luo, Jie Peng

“…The primary objective was to determine the optimal monitoring period for SOC. Within this period, optimal feature subsets were extracted using variable selection algorithms. …”
Get full text

The Application of Artificial Intelligent Algorithms in Electric Propulsion by Tian Bin, An Bingchen, Xie Kan, Yang Sulan

“…These studies not only demonstrate the great potential of artificial intelligence algorithms in enhancing the performance of electric propulsion systems, optimizing design, and reducing computational costs, but also provide new directions for the future development of electric propulsion technologies.…”
Get full text

Subsampling Algorithms for Irregularly Spaced Autoregressive Models by Jiaqi Liu, Ziyang Wang, HaiYing Wang, Nalini Ravishanker

“…These methods use A-optimality or D-optimality criteria to assess the usefulness of each data point and prioritize the inclusion of the most informative ones. …”
Get full text

Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…Results demonstrate that the CNN-LSTM-BMO achieves superior performance with the lowest Root Mean Square Error (RMSE) of 0.5523 and highest R² value of 0.9435, showing statistically significant improvements over other optimization methods as confirmed by paired t-tests (P < 0.05). …”
Get full text

Mathematical Models for Management Information Systems on Digital Platforms: from Resource Management to Demand Forecasting by Viktor Godliuk

“…The use of optimization methods, graph algorithms, forecasting, and machine learning to improve the efficiency of digital systems is investigated. …”
Get full text

A Quantum-Inspired Optimization Strategy for Optimal Dispatch to Increase Heat and Power Efficiency by K. Vanitha, B. Jyothi, R. Seshu Kumar, V. S. Chandrika, Arvind R. Singh, R. M. Naidoo

“…Future research can further explore the application of quantum-inspired optimization algorithms in other energy systems and optimize the algorithm’s parameters to improve its performance.…”
Get full text

Spatio-Temporal Joint Planning for Integrated Energy Systems with Internet Data Center Considering Privacy Preservation by WU Chengbang, CHENG Zhijiang, LU Haifeng, YANG Handi

“…Considering the privacy preservation requirements between the IDC and IES， an enhanced Benders decomposition algorithm for mixed-integer linear programming subproblems was improved， and a distributed solution framework was designed to solve the spatio-temporal joint planning model. …”
Get full text

Emergency evacuation paths for tank farm fires based on bi-objective dynamic planning by Guanbo Chou, Yili Duo, Jie Liu, Lin Sun, Yuyuan Zhang, Tie Sun

“…The BODP method includes both an equivalent rule proposed for the first time based on the linear weighting method, and an improved Dijkstra algorithm designed in this paper. …”
Get full text

A Method for Service Function Chain Migration Based on Server Failure Prediction in Mobile Edge Computing Environment by Joelle Kabdjou, Norihiko Shinomiya

“…Using a Long Short-Term Memory (LSTM) algorithm optimized by Super SAPSO (Simulated Annealing Particle Swarm Optimization), the model forecasts server failures with improved accuracy, reducing False Alarm Rates and improving Failure Detection Rates. …”
Get full text

Numerical thermodynamic-economic study and machine learning-based optimization of an innovative biogas-driven integrated power plant combined with sustainable liquid CO2 and liquid... by Ruijia Yuan, Fan Shi, Azher M. Abed, Mohamed Shaban, Sarminah Samad, Ahmad Almadhor, Barno Abdullaeva, Mouloud Aoudia, Salem Alkhalaf, Samah G. Babiker

“…In industrial environments, it effectively optimizes energy use and production processes by examining various operational factors, which leads to cost reductions and improved efficiency via predictive maintenance and cohesive energy strategies. …”
Get full text

Fleet Size and Mix Vehicle Routing Problem (FSMVRP), Adapted Large Neighbourhood Search Heuristic Optimization ProposalWith a Plant-capacity and Multi-day Planning Algorithm: A Liv... by Alperen Ekrem Çelikdin

Get full text