An ensemble of deep representation learning with metaheuristic optimisation algorithm for critical health monitoring using internet of medical things by Mai Alduailij

“…For the feature selection process, the binary grey wolf optimization (BGWO) model is employed to identify and retain the most significant features in the dataset. …”
Get full text

INNOVATIVE MECHANISMS FOR IMPLEMENTING STATE ECONOMIC POLICY FOR POST-WAR RECONSTRUCTION OF UKRAINE: QUANTUM TRANSFORMATIONS AS A DRIVER OF DEVELOPMENT by Oleksiy Shkuratov, Liudmila Antonova, Roman Dzyuba

“…The quantum transformation of Ukraine's economy in the conditions of post-war recovery can become an important component of the state investment policy, which will stimulate innovative development and increase the country's competitiveness in the international arena. …”
Get full text

Research Progress on Machine Learning Prediction of Compressive Strength of Nano-Modified Concrete by Ruyan Fan, Ankang Tian, Yikun Li, Yue Gu, Zhenhua Wei

“…Nano-modified concrete has attracted wide attention due to its improved mechanical properties. Among them, compressive strength is the most critical indicator. …”
Get full text

Reliability evaluation of dynamic face recognition systems based on improved Fuzzy Dynamic Bayesian Network by Zhiqiang Liu, Wenbo Zhu, Hongzhou Zhang, Shengjin Wang, Lu Fang, Weijun Hong, Hua Shao, Guopeng Wang

“…In this article, we propose a novel evaluation method with True Positive Identification Rate in dynamic and M:N mode and create a novel evaluation model of system reliability with the improved Fuzzy Dynamic Bayesian Network. Subsequently, we infer to solve the fuzzy reliability state probabilities of the six systems with Netica and get two most important factors with the improved fuzzy C-means algorithm. …”
Get full text

Optimizing Fairness and Spectral Efficiency With Shapley-Based User Prioritization in Semantic Communication by Moirangthem Tiken Singh, Adnan Arif, Rabinder Kumar Prasad, Bikramjit Choudhury, Chandan Kalita, Sikdar Md. S. Askari

“…The Shapley-based approach outperforms established methods, including the Hungarian algorithm, reinforcement learning algorithms like Deep Q-Network (DQN) and Proximal Policy Optimization (PPO), as well as conventional 4G and 5G resource allocation strategies. …”
Get full text

Numerical Investigation and Optimization of Transpiration Cooling Plate Structures with Combined Particle Diameter by Dan Wang, Yaxin Liu, Xiang Zhang, Mingliang Kong, Hanchao Liu

“…Further optimization with the multi-objective genetic algorithm (MOGA) determines the optimal structural parameters. …”
Get full text

Machine-Learning-Algorithm-Assisted Portable Miniaturized NIR Spectrometer for Rapid Evaluation of Wheat Flour Processing Applicability by Yuling Wang, Chen Zhang, Xinhua Li, Longzhu Xing, Mengchao Lv, Hongju He, Leiqing Pan, Xingqi Ou

“…By employing an improved whale optimization algorithm (iWOA) coupled with a successive projections algorithm (SPA), we selected the 20 most informative wavelengths (MIWs) from the full range spectra, allowing the iWOA/SPA-SOA-SVR model to predict SV with correlation coefficient and root-mean-square errors in prediction (R_P and RMSE_P) of 0.9605 and 0.2681 mL. …”
Get full text

Comprehensive Performance-Oriented Multi-Objective Optimization of Hemispherical Resonator Structural Parameters by Xiaohao Liu, Xin Jin, Chaojiang Li, Yumeng Ma, Deshan Xu, Simin Guo

“…Subsequently, the NSGA-II algorithm is applied to perform multi-objective mapping of these parameters, achieving an optimized resonator with a 4.61% increase in the minimum frequency difference from interference modes and a substantial improvement in thermoelastic damping of approximately 70.41%. …”
Get full text

An AI-based automatic leukemia classification system utilizing dimensional Archimedes optimization by Warda M. Shaban

“…We feed these extracted features to FSS, which uses a proposed method to select the most important and effective features. The proposed method is called the Dimensional Archimedes Optimization Algorithm (DAOA). …”
Get full text

Applications of Recent Metaheuristic Algorithms for Loss Reduction in Distribution Power Systems considering Maximum Penetration of Photovoltaic Units by Le Duy Luan Nguyen, Phuc Khai Nguyen, Viet Cuong Vo, Ngoc Dieu Vo, Thang Trung Nguyen, Tan Minh Phan

“…Photovoltaic units (PVUs) are placed optimally by implementing the Coot optimization algorithm (COOA), the archimedes optimization algorithm (AOA), the transient search optimization algorithm (TSOA), the crystal structure algorithm (CrSA), the war strategy optimization algorithm (WSA), and the average and subtraction-based optimizer (ASBO). …”
Get full text

Location Optimization Model of a Greenhouse Sensor Based on Multisource Data Fusion by DianJu Qiao, ZhenWei Zhang, FangHao Liu, Bo Sun

“…In this paper, a model based on the moving least square method in the fusion algorithm is proposed to study the optimal monitoring point of the sensor in the greenhouse and determine the most suitable installation position of the sensor in the greenhouse to improve the control effect of the temperature control device of the system. …”
Get full text

Color Dominance-Based Polynomial Optimization Segmentation for Identifying Tomato Leaves and Fruits by Juan Pablo Guerra Ibarra, Francisco Javier Cuevas de la Rosa, Alicia Linares Ramirez

“…Similarly, a UNetmodel is used for semantic segmentation, the results of which are inferior to those obtained by the proposed interpolation optimization method. The most significant contribution of the interpolation method is that it requires only a single iteration to generate the initial data, in contrast to the iterative search required by the greedy algorithm and the lengthy training process and video card dependency of the UNet model. …”
Get full text

Research on Optimization of Large-Scale Heterogeneous Combat Network Based on Graph Embedding by Xianzheng Meng, Changrong Xie, Hui Li, Guangjun Zeng, Kebin Chen

“…It has shown a 17.23% improvement in this aspect compared to HCNOF0 and a 6.89% enhancement when compared to the GE-SU-EANet algorithm, underscoring its advantages in both optimization performance and cost reduction. …”
Get full text

Contextual Regularization-Based Energy Optimization for Segmenting Breast Tumor in DCE-MRI by Priyadharshini Babu, Mythili Asaithambi, Sudhakar Mogappair Suriyakumar

“…An iterative gradient descent algorithm is engaged to minimize the energy-based cost function, obtaining stable convergence towards the optimal solution. …”
Get full text

Spatial modeling of brine level and salinity in the Qarhan Salt Lake using GIS and automated machine learning algorithms by Dongmei Yu, Zitao Wang, Chao Yue, Jianping Wang

Get full text

SIMULATION AND OPTIMIZATION AS A TOOL FOR THE DEVELOPMENT OF HIGH EFFECTIVE TECHNOLOGICAL SCHEMES OF DISTILLATION by A. V. Timoshenko, E. A. Anokhina

“…The data are presented for the optimization algorithms of the PTCDS. A comparison is made of conventional and developed distillation schemes using the energy consumption criterion. …”
Get full text

Towards few-shot learning with triplet metric learning and Kullback-Leibler optimization by Yukun Liu, Xiaojing Wei, Daming Shi, Dan Xiang, Junliu Zhong, Hai Su

“…In training, the deep learning and expectation-maximization algorithm are used to optimize models. Intensive experiments have been conducted on three popular benchmark datasets, and the experimental results show that this method significantly improves the classification ability of few-shot learning tasks and obtains the most advanced performance.…”
Get full text

Predicting compressive strength of concrete at elevated temperatures and optimizing its mixture proportions by Jinjun Xu, Han Wang, Wenjun Wu, Lang Lin, Yong Yu

“…The Cuckoo search algorithm was then employed to optimize mix designs, balancing high-temperature strength, cost and sustainability. …”
Get full text

Optimizing the lifetime of wireless sensor networks via reinforcement-learning-based routing by Wenjing Guo, Cairong Yan, Ting Lu

“…Reinforcement-learning-based routing protocol takes advantage of the intelligent algorithm of reinforcement learning to search for the optimal routing path for data transmission. …”
Get full text

Research on Multi-Objective Coordinated Planning of Distribution Networks Based on Improved Generative Adversarial Networks by Li Zhu

“…Next, a bi-level distribution network planning model considering carbon footprints is established: the upper level minimizes the annual comprehensive cost by optimizing the planning schemes of distributed generation (DG), energy storage systems (ESS), and capacitor banks (CB); the lower level minimizes operating costs, voltage deviations, and carbon emissions by formulating operation strategies under typical scenarios, considering on-load tap changers (OLTC), controllable loads, capacitor banks, energy storage, and distributed generation. …”
Get full text