Reservoir water level prediction using combined CEEMDAN-FE and RUN-SVM-RBFNN machine learning algorithms by Lan-ting Zhou, Guan-lin Long, Can-can Hu, Kai Zhang

“…This study proposed a method for reservoir water level prediction based on CEEMDAN-FE and RUN-SVM-RBFNN algorithms. By integrating the adaptive complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method and fuzzy entropy (FE) with the new and highly efficient Runge–Kuta optimizer (RUN), adaptive parameter optimization for the support vector machine (SVM) and radial basis function neural network (RBFNN) algorithms was achieved. …”
Get full text

Computer-Driven Assessment of Weighted Attributes for E-Learning Optimization by Olga Ovtšarenko, Elena Safiulina

“…Using artificial intelligence for data analytics, computer-based assessment improves efficiency, accuracy, and optimization of learning across disciplines. …”
Get full text

Courier Assignment and Routing Problem Algorithm in Online Food Delivery System with Multi-Customer Delivery Patterns by Prita Meilanitasari, Maulin Masyito Putri, Ilda Auly Sita Agustin, Muhammad Faisal Ibrahim, Dwi Sekar Arumjani

“…After processing and analyzing the numerical data, the study identified the most effective scenario that led to improved delivery times and benefits for couriers, enabling them to manage more orders and achieve faster delivery compared to existing algorithms. …”
Get full text

The impact of cultural factors on digital marketing strategies with Machine learning and honey bee Algorithm (HBA) by Muhammad Khan, Masood Ahmad, Rakhmonov Dilshodjon Alidjonovich, Kalonov Mukhiddin Bakhritdinovich, Kurbanbekova Mohichehra Turobjonovna, Imomov Jamshidxon Odilovich

“…This paper analyses the impact of cultural factors on digital marketing strategies in Pakistan. Improvement of machine learning (ML) techniques combined with the Honey Bee Algorithm (HBA) has been incorporated for better solutions. …”
Get full text

Multi-Source Data-Driven Terrestrial Multi-Algorithm Fusion Path Planning Technology by Xiao Ji, Peng Liu, Meng Zhang, Chengchun Zhang, Shuang Yu, Bing Qi, Man Zhao

“…A dynamic-heuristic A* algorithm is proposed, incorporating traffic signals and congestion penalties, and is enhanced by a DQN-based local decision module to improve adaptability to dynamic environments. …”
Get full text

Application of harmony search algorithm in optimizing autoregressive integrated moving average: A study on a data set of Coronavirus Disease 2019 by Riya Karmakar, Sandip Chatterjee, Debabrata Datta, Dipankar Chakraborty

“…ARIMA is one such model that has been widely used for this purpose, but in most cases, the model was not optimized suitably. …”
Get full text

SAMFA: A Flame Segmentation Algorithm for Infrared and Visible Aerial Images in the Same Scene by Jianye Yuan, Min Yang, Haofei Wang, Xinwang Ding, Song Li, Wei Gong

“…In response to the issues of poor flame segmentation performance in the current fire images and the large number of learnable parameters in large models, we propose an improved large model algorithm, SAMFA (Segmentation Anything Model, Fire, Adapter). …”
Get full text

Mesosphere data assimilation based on the intelligent optimization of the uncertainty parameters in a theoretical model by Dexin Ren, Jiuhou Lei, Xuetao Chen, Tong Dang, Yu Liu

“…In this study, we conducted an intelligent optimization particle filtering algorithm to optimize the uncertainty parameters in a physics-based model, which was used to simulate the terrestrial mesosphere. …”
Get full text

Control Optimization of Steam Boilers via Reinforcement Learning by Emmanuel Okafor, Maad Alowaifeer

“…Extensive experimental validation confirms the superiority of hybrid controllers, achieving significantly faster settling times, peak overshoot reductions to <inline-formula> <tex-math notation="LaTeX">$(\leq 2\%)$ </tex-math></inline-formula>, and lower error metrics than MRAC alone. While optimized PID serves as a baseline, hybrid controllers consistently achieve faster settling times and improved robustness under most nonlinear operating conditions. …”
Get full text

Path Optimization Model for Urban Transportation Networks under the Perspective of Environmental Pollution Protection by Can Liu, Zongping Li, Yueyang Li

“…Finally, the improved particle swarm optimization algorithm is used to solve the two-objective model to obtain the Pareto front solution set, that is, the path scheme under real-time traffic conditions. …”
Get full text

Multi-Objective Evolution and Swarm-Integrated Optimization of Manufacturing Processes in Simulation-Based Environments by Panagiotis D. Paraschos, Georgios Papadopoulos, Dimitrios E. Koulouriotis

“…Multiple objective functions are formulated to optimize the behavior of the system by reducing the work-in-progress items and improving both cost-effectiveness and service level. …”
Get full text

Algorithm for Constructing the Hazard Function of the Extended Cox Model and its Application to the Prostate Cancer Patient Database by I. I. Mikulik, G. M. Zharinov, A. Yu. Kneev

“…The quality of training of the Cox model was assessed by C-index.Results. A metaheuristic algorithm for ant pollinator optimizing was proposed, providing for the construction of hazard functions of the extended Cox model. …”
Get full text

A Novel, Self-Adaptive, Multiclass Priority Algorithm with VM Clustering for Efficient Cloud Resource Allocation by Hicham Ben Alla, Said Ben Alla, Abdellah Ezzati, Abdellah Touhafi

“…The simulation results and analysis demonstrate that the proposed algorithm effectively optimizes makespan and energy consumption. …”
Get full text

Evolutionary Cost Analysis and Computational Intelligence for Energy Efficiency in Internet of Things-Enabled Smart Cities: Multi-Sensor Data Fusion and Resilience to Link and Devi... by Khalid A. Darabkh, Muna Al-Akhras

“…Thorough simulations and comparative analysis reveal the protocol’s superior performance across key performance metrics, namely, network lifespan, energy consumption, throughput, and average delay. When compared to the most recent and relevant protocols, including the Particle Swarm Optimization-based energy-efficient clustering protocol (PSO-EEC), linearly decreasing inertia weight PSO (LDIWPSO), Optimized Fuzzy Clustering Algorithm (OFCA), and Novel PSO-based Protocol (NPSOP), our approach achieves very promising results. …”
Get full text

Enhanced probabilistic prediction of pavement deterioration using Bayesian neural networks and cuckoo search optimization by Feng Xiao, Biying Shi, Jie Gao, Huapeng Chen, Di Yang

“…Therefore, this study proposed an improved probabilistic model for pavement deterioration prediction based on the coupling of Bayesian neural network (BNN) and cuckoo search (CS) algorithm. …”
Get full text

A Real-time Speed Profile Planning Algorithm for Freight Trains Based on Neural Network by ZHU Yuqing, BAI Baoxue, CHEN Honghui, CHEN Nankuang, WANG Qingyuan

“…Firstly, the algorithm determines the input and output forms of the neural network model by analyzing the optimization results of the quadratic programming, and then trains the neural network model with a large number of optimization results as sample data to determine the structure and weights of the model. …”
Get full text

Optimized Adaptive Fuzzy Synergetic Controller for Suspended Cable-Driven Parallel Robots by Yasser Hatim Alwan, Ahmed A. Oglah, Muayad Sadik Croock

“…The parameters of the controller are optimized using the Dragonfly Algorithm, a metaheuristic technique known for its simplicity and fast convergence. …”
Get full text

Optimizing Curriculum for Students: A Machine Learning Approach to Time Management Analysis by Jianmin Dong

“…Additionally, Tasmanian Devil Optimization (TDO) and Equilibrium Slime Mould Algorithm (ESMA) are integrated to enhance the accuracy of both XGBC and HGBC models. …”
Get full text

Artificial Flora Algorithm-Based Feature Selection With Support Vector Machine for Cardiovascular Disease Classification by M. M. Asha, G. Ramya

“…This approach utilizes the Cleveland dataset by combining the Artificial Flora Optimization algorithm with the Support Vector Machine. …”
Get full text

Enhanced Crop Leaf Area Index Estimation via Random Forest Regression: Bayesian Optimization and Feature Selection Approach by Jun Zhang, Jinpeng Cheng, Cuiping Liu, Qiang Wu, Shuping Xiong, Hao Yang, Shenglong Chang, Yuanyuan Fu, Mohan Yang, Shiyu Zhang, Guijun Yang, Xinming Ma

“…This framework employs a tree model-based feature selection method to identify critical features, reducing redundancy and improving model interpretability. …”
Get full text