Proactive Data Placement in Heterogeneous Storage Systems via Predictive Multi-Objective Reinforcement Learning by Suchuan Xing, Yihan Wang

“…Existing tiered storage systems predominantly employ reactive policies that respond to observed access patterns, leading to suboptimal performance under dynamic workloads and failing to address multi-objective optimization requirements. We propose a novel proactive data placement framework that integrates predictive deep learning with multi-objective reinforcement learning to anticipate future data access patterns and optimize placement decisions across storage hierarchies. …”
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LazyAct: Lazy actor with dynamic state skip based on constrained MDP. by Hongjie Zhang, Zhenyu Chen, Hourui Deng, Chaosheng Feng

“…Inspired by human decision-making patterns, which involve reasoning only on critical states in continuous decision-making tasks without considering all states, we introduce the LazyAct algorithm. This algorithm significantly reduces the number of inferences while preserving the quality of the policy. …”
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A User-Priority-Driven Multi-UAV Cooperative Reconnaissance Strategy by Zeyuan Liu, Cuntao Liu, Wendong Zhao, Aijing Li

“…This reconnaissance process is formulated as a cooperative path planning problem, where the optimization objective is maximizing users’ total satisfaction, while an intelligent algorithm is proposed to solve this problem effectively. …”
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About a Routing Problem of the Tool Motion on Sheet Cutting by A. A. Petunin, A. G. Chentsov, P. A. Chentsov

“…An optimal procedure based on the dynamic programming and an effective heuristic algorithm realized on a multicore computer are proposed. …”
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Vulnerability Assessment in Karst Aquifers with EPIK and COP Indices Calibration by Hamid Kardan Moghadam, Amir Reza Nemati Mansour, Abbas Akbarzadeh, Ali Mirarabi

“…In order to calibrate the GQI qualitative index with the zoning of the springs in the region, whale optimization algorithms were used. In this calibration, the weights and ranks of the two vulnerability indices were determined. …”
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Classification-based point cloud denoising and 3D reconstruction of roadways by Denghong CHEN, Ning PANG, Wen NIE, Juqiang FENG, Jiliang KAN, Jinjing ZHANG

“…This algorithm delivered adaptive optimization performance, yielding types Ⅰ and Ⅱ errors of 1.54 % and 5.37 %, respectively. …”
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Obstacle Avoidance Control of Autonomous Undersea Vehicle Based on DVFH+ in Ocean Current Environment by Zhongben ZHU, Jiahao ZHANG, Yifan XUE, Hongde QIN

“…Additionally, by considering the drift angle compensation in the real ocean current environment, the obstacle avoidance algorithm was optimized to improve its robustness and adaptability. …”
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A novel pulse-current waveform circuit for low-energy consumption and low-noise transcranial magnetic stimulation by Xinhua Tan, Ao Guo, Jiasheng Tian, Yingwei Li, Yingwei Li, Jian Shi

“…This study proposes a novel, non-resonant, high-frequency switching design controlled by high-frequency pulse-width modulation (PWM) voltage excitation to achieve ideal pulse-current waveforms that minimize both clicking noise and heat generation from the TMS coil.MethodFirst, a particle swarm optimization algorithm was used to optimize the pulse-current waveform, minimizing both the resistance loss and clicking noise (vibration energy) generated by the TMS coils. …”
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Hybrid A*-Guided Model Predictive Path Integral Control for Robust Navigation in Rough Terrains by Joonyeol Yang , Minhyeong Kang , Seulchan Lee, Sanghyun Kim

“…These computed paths are then used to define the mean control input for the MPPI algorithm, which performs localized optimization while adhering to the terrain-aware trajectory. …”
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Evaluation of Multi-Class Classification Performance Lung Cancer Through K-NN and SVM Approach by Muh. Indra Endriartono Saputra Troy, Sitti Rahmah Jabir, Siska Anraeni

“…Therefore, the results show that the SVM algorithm is superior to the KNN algorithm. The KNN and SVM methods were implemented for multi-class classification of lung cancer, allowing identification of various subtypes of lung cancer with optimal accuracy.…”
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Digital three-stage recursive-separable image processing filter with variable sizes of scanning multielement aperture by A. V. Kamenskiy, T. M. Akaeva, D. A. Grebenshchikova

“…The study established that the processing time of a test image using the developed filter is on average 5 times less than the time taken by the classical two-dimensional convolution algorithm. The optimal coefficients for magnifying the central element and raising the positive part of the aperture of a digital filter were determined, enabling the efficiency of its use to be enabled.Conclusions. …”
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Steatotic liver disease: radiological and ultrasound point of view by Alexey V. Borsukov, Daria Yu. Shestakova

“…All patients were examined with a single diagnostic algorithm consisting of 5 stages: clinical and laboratory stage, physical examination, ultrasound, dual-energy X-ray absorptiometry in the “Whole Body” mode, retrospective analysis of MDCT and/or MRI studies. …”
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Reconstruction of Tissue-Specific Metabolic Networks Using CORDA. by André Schultz, Amina A Qutub

“…Here we introduce a novel algorithm called Cost Optimization Reaction Dependency Assessment (CORDA) to build genome scale models in a tissue-specific manner. …”
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Adaptive Forming of the Beam Pattern of Microstrip Antenna with the Use of an Artificial Neural Network by Janusz Dudczyk, Adam Kawalec

“…This paper presents the training neural network algorithm with the selection of optimal network structure. …”
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Efficient Energy Management in Wireless Sensor Networks Using Edge Sensor Node-Based Routing Protocols by Dhari Ali Mahmood, Yahiea Al Naiemy

“…The process of node selection take into consideration in EEERP, where the node with low energy level automatically assigned new ESN, to ensuring continuous network operation and optimal performance. Analysis of the EEERP results validate through MATLAB simulation to compareing it against established protocols such as the performance efficient data aggregation protocol(PEDAP) and high quality of service routing algorithm(HQRA). …”
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Game Theoretic Non‐cooperative Dynamic Target Tracking for Directional Sensing‐Enabled Unmanned Aerial Vehicles by Peng Yi, Ge Jin, Wenyuan Wang

“…Game theory is employed to determine the optimal confrontation paths for defenders against the intruders. …”
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A hybrid blockchain-based solution for secure sharing of electronic medical record data by Gang Han, Yan Ma, Zhongliang Zhang, Yuxin Wang

“…This algorithm not only streamlines the signature process across chains but also strengthens system security and optimizes storage efficiency, addressing a key challenge in multi-chain systems. …”
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Maintenance Scheduling Strategy for MMCs Within an MVDC System Using Sensitivity Analysis by Tae-Yang Nam, Dong-Il Cho, Joong-Woo Shin, Kwang-Hoon Yoon, Jae-Chul Kim, Won-Sik Moon

“…The proposed algorithm optimizes the maintenance timing and priority by performing a sensitivity analysis of the system reliability indicators, from both the consumer and operator perspectives. …”
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GTrXL-SAC-Based Path Planning and Obstacle-Aware Control Decision-Making for UAV Autonomous Control by Jingyi Huang, Yujie Cui, Guipeng Xi, Shuangxia Bai, Bo Li, Geng Wang, Evgeny Neretin

“…Experimental results in the AirSim drone simulation environment demonstrate that compared to PPO and SAC algorithms, GTrXL-SAC achieves more precise policy exploration and optimization, enabling superior control of drone velocity and attitude for stabilized flight while accelerating convergence speed by nearly 20%.…”
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Aircraft Flight Autonomous Decision-Making Method Based on Target Predicted Trajectory and Markov Decision Process by Yang Zhou, Xinmin Tang, Xuanming Ren

“…Secondly, we adopt the Markov Decision Process as the autonomous decision-making method for the own aircraft, proposing a method by which to calculate the optimal decision sequence based on the prediction scenarios of the IMM algorithm; that is, in both multi-step prediction and single-step prediction scenarios, the payoff values of different action strategies at each decision moment are calculated to obtain the optimal decision sequence. …”
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