Malware detection approach based on improved SOINN by Bin ZHANG, Lixun LI, Shuqin DONG

“…To deal with the problems of dynamic update of detection model and high computation costs in malware detection model based on batch learning,a novel malware detection approach is proposed by combing SOINN and supervised classifiers,to reduce computation costs and enable the detection model to update dynamically with the assistance of SOINN′s incremental learning characteristic.Firstly,the improved SOINN was given.According to the whole alignment algorithm,search the adjusted weights of neurons under all input sequences in the learning cycle and then calculate the average value of all adjusted weights as the final result,to avoid SOINN′s stability under different input sequences and representativeness of original data,therefore improve malware detection accuracy.Then a data preprocessing algorithm was proposed based on nonnegative matrix factor and Z-score normalization to transfer the malware behavior feature vector from high dimension and high order to low dimension and low order,to speed up and avoid overfitting and further improve detection accuracy.The results of experiments show that proposed approach supports dynamic updating of detection model and has a significantly higher accuracy of detecting unknown new samples and lower computation costs than tradition methods.…”
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Augmentation and Classification of Requests in Moroccan Dialect to Improve Quality of Public Service: A Comparative Study of Algorithms by Hajar Zaidani, Rim Koulali, Abderrahim Maizate, Mohamed Ouzzif

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Improving of the Generation Accuracy Forecasting of Photovoltaic Plants Based on <i>k</i>-Means and <i>k</i>-Nearest Neighbors Algorithms by P. V. Matrenin, A. I. Khalyasmaa, V. V. Gamaley, S. A. Eroshenko, N. A. Papkova, D. A. Sekatski, Y. V. Potachits

“…One of the ways to improve the accuracy of forecast models is a deep analysis of meteorological conditions as the main factor affecting the power generation. …”
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Multi-UAV Delivery Path Optimization Based on Fuzzy C-Means Clustering Algorithm Based on Annealing Genetic Algorithm and Improved Hopfield Neural Network by Song Liu, Di Liu, Meilong Le

“…This study develops an MTSP model for multi-UAV delivery optimization from a central hub, proposing a hybrid algorithm that integrates genetic simulated annealing-enhanced clustering with an improved Hopfield neural network to minimize the total flight distance. …”
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Intelligent Teaching Recommendation Model for Practical Discussion Course of Higher Education Based on Naive Bayes Machine Learning and Improved <i>k</i>-NN Data Mining Algorithm by Xiao Zhou, Ling Guo, Rui Li, Ling Liu, Juan Pan

“…Based on the encoding tree model, an improved <i>k</i>-NN algorithm recommendation model is established to match the student group interests and recommend discussion topics. …”
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The Path Tracking Control of Unmanned Surface Vehicles Based on an Improved Non-Dominated Sorting Genetic Algorithm II-Based Multi-Objective Nonlinear Model Predictive Control Method by Yunzhe Guo, Qidan Zhu, Jinyou Mou

“…This paper proposes a multi-objective nonlinear model predictive control (MOMPC) method based on an improved non-dominated sorting genetic algorithm II (NSGAII) for the path tracking problem of unmanned surface vehicles (USVs). …”
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An Improved KNN-Based Slope Stability Prediction Model by Shuai Huang, Mingming Huang, Yuejun Lyu

“…In our study, the k-nearest neighbor (KNN) algorithm is improved to reduce its sample dependence and improve the robustness of the algorithm, and then the prediction model of the slope stability is proposed based on the improved k-nearest neighbor (KNN) algorithm. …”
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Frequency minimum inertia calculation of complex power systems based on an improved simulated annealing algorithm by Qiang Zhang, Qi Jia, Tingqi Zhang, Hui Zeng, Chao Wang, Wansong Liu

“…It is also suggested that more uncertainty factors can be considered in the future to improve the model and algorithm and enhance the practicality and adaptability.…”
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Prediction method of soil water content based on SVM optimized by improved salp swarm algorithm by Xiaoqiang ZHAO, Fan YANG, Zhufeng YAN

“…Aiming at the problems of low accuracy and low efficiency of traditional soil water content prediction methods, support vector machine (SVM) was used to establish a prediction model, and the soil water content prediction method based on SVM optimized was proposed by the improved salp swarm algorithm.Firstly, the opposition-based learning and chaotic optimization were introduced to improve the standard salp swarm algorithm to solve the problem that the algorithm was easy to fall into the local optimal solution and its convergence speed was slow.Secondly, the improved salp swarm algorithm was used to optimize the parameters that affect the performance of SVM and the corresponding prediction model was built.Finally, the proposed model was compared with the particle swarm optimization SVM and the whale algorithm optimized SVM prediction model.The experimental results show that the mean square error and decision coefficient of the proposed model are 0.42 and 0.901, which are better than the other two models which verified the effectiveness of the proposed method.…”
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Prediction method of soil water content based on SVM optimized by improved salp swarm algorithm by Xiaoqiang ZHAO, Fan YANG, Zhufeng YAN

“…Aiming at the problems of low accuracy and low efficiency of traditional soil water content prediction methods, support vector machine (SVM) was used to establish a prediction model, and the soil water content prediction method based on SVM optimized was proposed by the improved salp swarm algorithm.Firstly, the opposition-based learning and chaotic optimization were introduced to improve the standard salp swarm algorithm to solve the problem that the algorithm was easy to fall into the local optimal solution and its convergence speed was slow.Secondly, the improved salp swarm algorithm was used to optimize the parameters that affect the performance of SVM and the corresponding prediction model was built.Finally, the proposed model was compared with the particle swarm optimization SVM and the whale algorithm optimized SVM prediction model.The experimental results show that the mean square error and decision coefficient of the proposed model are 0.42 and 0.901, which are better than the other two models which verified the effectiveness of the proposed method.…”
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An Adaptive Layering Dual-Parameter Regularization Inversion Method for an Improved Giant Trevally Optimizer Algorithm by Chao Tan, Menghao Sun, Wei Liu, Wenrui Tan, Xiaoling Zhang, Chengang Zhu, Da Li

“…Subsequently, the current model parameters of the inversion objective function are optimized using the Giant Trevally Optimizer (GTO) algorithm, improved by the Particle Swarm Optimization (PSO) algorithm. …”
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Intelligent decision-making for mine airflow on demand based on the improved artificial bee colony algorithm by ZHANG Lang, LEI Shuang, LI Wei, LIU Yanqing

“…To address the issue of slow convergence speed in solving the unconstrained optimization mathematical model of mine airflow control using existing metaheuristic algorithms, an intelligent decision-making method for mine airflow on demand based on an improved Artificial Bee Colony (ABC) algorithm was proposed. …”
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A Lightweight Algorithm for Detection and Grading of Olive Ripeness Based on Improved YOLOv11n by Fengwu Zhu, Suyu Wang, Min Liu, Weijie Wang, Weizhi Feng

“…To address these limitations, this study proposes a lightweight algorithm for detection and grading of olive ripeness based on an Improved YOLOv11n framework. …”
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Research on Food Image Classification Algorithm based on Improved MobileNetV3-Large by HE Wei-chan, YANG Zhi-jing, QIN Jing-hui

“…In order to address these issues, this paper proposed a food image classification algorithm based on improved MobileNetV3-Large. Firstly, building upon the pre-trained MobileNetV3-Large model, the PReLu activation function and NAM attention mechanism were introduced to enhance the model's focus on key features by capturing non-local dependencies in images. …”
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Research on timing method for single intersection in transportation Internet of things based on improved Webster algorithm by Lin MA, Fuyang CHEN, Bin JIANG

“…Aiming at the timing signal problem of single intersection,a timing method based on the improved Webster algorithm in transportation Internet of things was proposed by combining the micro level analysis method with the macro level analysis method.In order to optimize the saturation and signal control delay,the average delay model was established.The game model and the conflict model were established with non-signal control and signal control.And the conflict analysis was carried out to illustrate that the optimal signal timing could coordinate the conflicting traffic flow.Based on the improved Webster algorithm,the shortest time required for the motor vehicle to pass the single intersection was additionally considered and a three-step optimization method for timing method at single intersection was proposed to reduce the traffic delay to ensure that the vehicle could pass effectively.The simulation results illustrate the effectiveness of the proposed solution.…”
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Bi-objective Rolling Operation Optimization Based on Surrogate Model Acceleratiy of Community-Level Integrated Energy Systems by Xiaoman HU, Weikun TIAN, Guanyu SONG, Hao YU

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DV-DETR: Improved UAV Aerial Small Target Detection Algorithm Based on RT-DETR by Xiaolong Wei, Ling Yin, Liangliang Zhang, Fei Wu

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Distributed Photovoltaic Power Energy Generation Prediction Based on Improved Multi-objective Particle Algorithm by Yuanzheng Xiao, Huawei Hong, Feifei Chen, Xiaorui Qian, Ming Xu, Hanbin Ma

“…A hybrid LSTM-PSO model was created, where the LSTM network served as the core prediction model, and the improved MO-PSO algorithm optimized its hyperparameters, enhancing generalization and avoiding overfitting. …”
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Disease Detection Algorithm for Tea Health Protection Based on Improved Real-Time Detection Transformer by Zhijie Lin, Zilong Zhu, Lingling Guo, Jingjing Chen, Jiyi Wu

“…While the precision improves, the FPS value also increases by 109, which is superior to the traditional model in terms of precision and real-time processing. …”
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Complex Environmental Geomagnetic Matching-Assisted Navigation Algorithm Based on Improved Extreme Learning Machine by Jian Huang, Zhe Hu, Wenjun Yi

“…To enhance the matching performance of the NGO-ELM algorithm, three improvements are proposed to the NGO algorithm. …”
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