Fire spread simulations using Cell2Fire on synthetic and real landscapes by Minho Kim, Cristobal Pais, Marta C. Gonzalez

“…In response, we used two optimization methods to improve the simulation’s accuracy. …”
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A low-carbon optimization scheduling method of CIES based on PPO algorithm by CHEN Fan, WU Lingxiao, WANG Man, LYU Ganyun, ZHANG Xiaolian

“…The tiered carbon trading mechanism and optimization scheduling model solving algorithm are pivotal for the community integrated energy system (CIES). …”
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Optimizing firefighting resilience in airports through genetic algorithms and decision-making frameworks by Yulong Zhu, Wei Tian, Xuhong Jia, Quanyi Liu

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MULTI-MODEL STACK ENSEMBLE DEEP LEARNING APPROACH FOR MULTI-DISEASE PREDICTION IN HEALTHCARE APPLICATION by Bhaskar Adepu, T. Archana

“…This model integrates pre-processing techniques and employs the Tuna Swarm Optimization (TSO) Algorithm for feature selection in executing multi-label disease prediction. …”
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Mixed Time/Event-Triggered Model Predictive Tracking Control for Networked Mobile Robots by Huixin Liu, Yonghua Lai, Hongsong Lian, Guobin Wang, Dongsheng Zheng

“…Focusing on the tracking control challenges in networked mobile robot systems, this research formulates a mixed time/event-triggered model predictive control (MPC) method. The method integrates time-triggered and event-triggered mechanisms, where the time-triggered module improves the performance of the MPC, and the event-triggered module reduces the resource consumption without sacrificing the control performance. …”
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A Mutual Algorithm for Optimizing Distributed Source Coding in Wireless Sensor Networks by Nashat Abughalieh, Kris Steenhaut, Bart Lemmens, Ann Now©

“…This paper presents contributions to the lifetime optimization problem of WSNs in the form of two algorithms: the Updated-CMAX (UCMAX) power-aware routing algorithm to optimize the routing tree and the Rate Optimization (RO) algorithm to optimize the encoding rates of the nodes. …”
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The algorithm of the engineering method of parameter optimization dump working equipment of the motor grader by Ignatov S.D.

“…This paper presents an analysis of existing motor grader blade equipment designs, develops an engineering methodology optimization algorithm, and examines the main stages of its implementation, including modeling, iterative optimization procedures, and experimental validation. …”
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Swarm Intelligence Algorithms for Optimization Problems a Survey of Recent Advances and Applications by Mande Smita Samrat, M Srinivasulu, Anand Sruthi, K Anuradha, Tiwari Mohit, U Esakkiammal

“…For many years swarm intelligence (SI) algorithms have shown successful performance for complex optimization problems in many fields. …”
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Balanced operation strategies of district heating systems based on dynamic hydraulic-thermal modeling by Xiaojie Lin, Ning Zhang, Zheng Luo, Encheng Feng, Wei Zhong

“…For the primary side network in the various operation conditions, the dynamic hydraulic-thermal model is established. The heating supply imbalance of the primary side return temperatures among different heating substations is defined and optimized based on the dynamic hydraulic-thermal model and the particle swarm optimization algorithm. …”
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Identifying liver cirrhosis in patients with chronic hepatitis B: an interpretable machine learning algorithm based on LSM by Xueting Bai, Chunwen Pu, Wenchong Zhen, Yushuang Huang, Qian Zhang, Zihan Li, Yixin Zhang, Rongxuan Xu, Zhihan Yao, Wei Wu, Mei Sun, Xiaofeng Li

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Optimization of a Time-of-Arrival-Ridge Estimation Iterative Model for Ultra-Wideband Positioning in a Long Linear Area by Mengqian Li, Mingduo Li, Jinhua Wang, Aoze Duan, Haotian Sun, Qinggang Meng

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Rainfall Prediction in Khorasan Razavi Stations Using a Hybrid Neural Network and Genetic Algorithm Approach by Mahdi Naseri, Mahsa Mardani

“…This study proposes a novel hybrid approach, combining the Non-linear Auto Regressive with eXogenous inputs (NARX) neural network with a Genetic Algorithm (GA) for parameter optimization, aiming to improve daily rainfall prediction in Khorasan Razavi province, Iran. …”
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Optimizing diabetic retinopathy detection with electric fish algorithm and bilinear convolutional networks by Udayaraju Pamula, Venkateswararao Pulipati, G. Vijaya Suresh, M. V. Jagannatha Reddy, Anil Kumar Bondala, Srihari Varma Mantena, Ramesh Vatambeti

“…To enhance classification accuracy, the system introduces a hybrid Electric Fish Optimization Arithmetic Algorithm (EFAOA), which refines the exploration phase, ensuring rapid convergence. …”
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The optimal route search in Bengaluru city transport using Hamilton circuit algorithm by Parkavi S, Parthiban A

“…So, drawing inspiration and motivation from the outstanding work of Mungporn, Pongsiri et al., “Modeling and control of multiphase interleaved fuel-cell boost converter based on Hamiltonian control theory for transportation applications, IEEE Transactions on Transportation Electrification 6.2, 2020, pp. 519-529”, in this paper, we study an intelligent agent model to perform route engineering for public transportation in the Bengaluru city, based on the Hamilton circuit algorithm and analyze the best and optimal route among the three significant routes out of twelve available using various parameters. …”
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An Ensemble Formal Approach to Improve Energy Efficiency and Data Aggregation in Smart Agriculture by Shahbaz Ahmad, Nadeem Akhtar, Adeel Ahmed, Saman Iftikhar, Shaikhan Bawazeer, Saima Abdullah

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Machine learning via DARTS-Optimized MobileViT models for pancreatic Cancer diagnosis with graph-based deep learning by Yusuf Alaca

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Optimizing Imbalanced Data Classification: Under Sampling Algorithm Strategy with Classification Combination by Nauval Dwi Primadya, Adhitya Nugraha, Sahrul Yudha Fahrezi, Ardytha Luthfiarta

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Joint beam hopping and coverage control optimization algorithm for multibeam satellite system by Guoliang XU, Feng TAN, Yongyi RAN, Feng CHEN

“…To improve the performance of multibeam satellite (MBS) systems, a deep reinforcement learning-based algorithm to jointly optimize the beam hopping and coverage control (BHCC) algorithm for MBS was proposed.Firstly, the resource allocation problem in MBS was transformed to a multi-objective optimization problem with the objective maximizing the system throughput and minimizing the packet loss rate of the MBS.Secondly, the MBS environment was characterized as a multi-dimensional matrix, and the objective problem was modelled as a Markov decision process considering stochastic communication requirements.Finally, the objective problem was solved by combining the powerful feature extraction and learning capabilities of deep reinforcement learning.In addition, a single-intelligence polling multiplexing mechanism was proposed to reduce the search space and convergence difficulty and accelerate the training of BHCC.Compared with the genetic algorithm, the simulation results show that BHCC improves the throughput of MBS and reduces the packet loss rate of the system, greedy algorithm, and random algorithm.Besides, BHCC performs better in different communication scenarios compared with a deep reinforcement learning algorithm, which do not consider the adaptive beam coverage.…”
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Application of artificial intelligence and red-tailed hawk optimization for boosting biohydrogen production from microalgae by Hegazy Rezk, Ali Alahmer, Abdul Ghani Olabi, Enas Taha Sayed

“…The introduction of fuzzy logic into the model significantly improves its predictive accuracy, as evidenced by the drop in RMSE from 10.79 with ANOVA to 0.7159 with ANFIS, representing a substantial 93.4 % decrease. …”
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Soft-sensor modeling of silicon content in hot metal based on sparse robust LS-SVR and multi-objective optimization by GUO Dong-wei, ZHOU Ping

“…Based on those, an on-line soft sensor model of hot metal[Si] with the optimal parameters was obtained by using the multi-objective genetic algorithm (NSGA-Ⅱ) with the non-dominated sort and elitist strategy. …”
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