Improving Model-Based Deep Reinforcement Learning with Learning Degree Networks and Its Application in Robot Control by Guoqing Ma, Zhifu Wang, Xianfeng Yuan, Fengyu Zhou

“…Deep reinforcement learning is the technology of artificial neural networks in the field of decision-making and control. The traditional model-free reinforcement learning algorithm requires a large amount of environment interactive data to iterate the algorithm. …”
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Dual-Resource Optimization Configuration and Collaborative Scheduling for Flexible Job Shop Under Worker Flexibility Constraints by Zijie Ren, Hongyi Qu, Mejdl Safran, Jiafu Wan

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Machine Learning-Based Prediction Performance Comparison of Marshall Stability and Flow in Asphalt Mixtures by Muhammad Farhan Zahoor, Arshad Hussain, Afaq Khattak

“…The potential of various machine learning (ML) algorithms to predict Marshall Stability (MS) and Marshall Flow (MF) was investigated in this work. …”
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Short‐term electric power and energy balance optimization scheduling based on low‐carbon bilateral demand response mechanism from multiple perspectives by Juan Li, Yonggang Li, Huazhi Liu

“…An optimal scheduling model of LCBDR is established. The enhanced decision tree classifier (EDTC) algorithm is used to predict the electricity consumption behavior of transferable load (TL) users, and an improved particle swarm optimization (PSO) algorithm with “ε‐greedy” strategy is proposed to solve this model. …”
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A Sensory Glove With a Limited Number of Sensors for Recognition of the Finger Alphabet of Polish Sign Language by Jakub Piskozub, Pawel Strumillo

“…The influence hierarchy of individual piezoelectric sensors was determined using a decision tree algorithm during previous stage of research, which achieved 94% accuracy with data from only three sensors. …”
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Feasibility of Licensed Vocational Nurses Using a CDS App to Communicate Signs and Symptoms of a UTI by Alyce S. Ashcraft, Donna C. Owen, Kyle Johnson, Huaxin Song

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KDFE: Robust KNN-Driven Fusion Estimator for LEO-SoOP Under Multi-Beam Phased-Array Dynamics by Jiaqi Yin, Ruidan Luo, Xiao Chen, Linhui Zhao, Hong Yuan, Guang Yang

“…Empirical analysis reveals that phased-array beamforming generates three-tiered SNR fluctuation patterns during unpredictable beam handovers, rendering conventional single-algorithm solutions fundamentally inadequate. …”
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Environmental performance driven optimization of urban modular housing layout in Singapore by Xiaoyu Shen, Xue Ye

“…This paper presents a performance-driven architectural design (PDAD) workflow for shape generation and genetic optimization based on environmental data, using public housing in the Singapore region as a case study. It integrates three-dimensional cellular automata, parametric performance simulation, genetic optimization algorithms, and hierarchical clustering algorithms. …”
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IMPLEMENTASI METODE RANDOM FOREST DALAM MEMPREDIKSI SINYAL PERGERAKAN SAHAM by MOCH. ANJAS APRIHARTHA, M. HUSNIYADI, TAUFIK NUR ALAM

“…Random forest is a combination algorithm of several decision trees used to solve prediction or classification problems. …”
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An Operation Optimization for Express Freight Trains Based on Shipper Demands by Yuzhao Zhang, Yusong Yan

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Study on the risk identification of abnormal gas outbursts based on the mechanism of biological immunity by Jufeng Zhang, Shiliang Shi, Lizhi Zhang

“…The results show: (1) The adaptive recognition algorithm based on T-B cell principles can adaptively recognize the characteristic vectors of abnormal gas outbursts by adaptive adjustment of detectors and cloning and mutation of learning vectors, achieving the recognition and memorization of known or unknown feature vectors under dynamically changing environmental conditions. (2) The adaptive recognition algorithm for abnormal gas outbursts based on T-B cell principles and the type recognition algorithm for abnormal gas outbursts based on the Dynamic Time Warping algorithm, combined with the characteristics of biological immune systems, construct a risk identification model for abnormal gas outbursts based on the biological immune mechanism, which has the characteristics of adaptability, learning, and memorization. (3) Taking a abnormal gas outburst event in a certain 9111 working face of a mine in Huaibei as an example, the model was verified by inputting the characteristic vectors of abnormal gas outbursts and the output of the risk identification of abnormal gas outbursts based on the biological immune mechanism. …”
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Bio-Inspired Observability Enhancement Method for UAV Target Localization and Sensor Bias Estimation with Bearing-Only Measurement by Qianshuai Wang, Zeyuan Li, Jicheng Peng, Kelin Lu

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Assessment of Risks of Voltage Quality Decline in Load Nodes of Power Systems by Pylyp Hovorov, Roman Trishch, Romualdas Ginevičius, Vladislavas Petraškevičius, Karel Šuhajda

“…At the same time, when making management decisions, three possible levels can be distinguished: decision-making in conditions of certainty, when the result is presented in a deterministic form and can be determined in advance; decision-making under conditions of risk, when the outcome cannot be determined in advance, but there is information on the probability of distribution of possible consequences; decision-making in conditions where the outcome is random and there is no information about the consequences of the decision. …”
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Modules of Organizational and Technical Systems for Solving Problems of Adaptation in a Rapidly Changing Environment by A. Mikryukov, V. M. Trembach, A. V. Danilov

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Multidimensional Evaluation Framework and Classification Strategy for Low-Carbon Technologies in Office Buildings by Hongjiang Liu, Yuan Song, Yawei Du, Tao Feng, Zhihou Yang

“…The method includes four core components: (1) establishing three archetypal models—low-rise (H ≤ 24 m), mid-rise (24 m < H ≤ 50 m), and high-rise (50 m < H ≤ 100 m) office buildings—based on 99 office buildings in Beijing; (2) classifying 19 key technologies into three clusters—Envelope Structure Optimization, Equipment Efficiency Enhancement, and Renewable Energy Utilization—using bibliometric analysis and policy norm screening; (3) developing a four-dimensional evaluation framework encompassing Carbon Reduction Degree (CRD), Economic Viability Degree (EVD), Technical Applicability Degree (TAD), and Carbon Intensity Degree (CID); and (4) conducting a comprehensive quantitative evaluation using the AHP-entropy-TOPSIS algorithm. …”
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Fuzzy Analytical Hierarchy Process Method to Determine the Quality of Gemstones by Mochammad Sobandi Dwi Putra, Septi Andryana, Fauziah, Aris Gunaryati

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A network-based approach on detecting dredgers’ illegal behavior of dumping dredged sediments by Rongxin Zhang, Fei Yuan, En Cheng

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Optimal Poisson Cognitive System with Markov Learning Model by A. A. Solodov

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A Multiobjective Mathematical Model for Truck Scheduling Problem in Multidoor Cross-Docking System by Mahziar Taghizadeh, Amir Abbas Shojaie, Amir Homayoun Sarfaraz, Sadigh Raissi

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Game-Theoretic Cooperative Task Allocation for Multiple-Mobile-Robot Systems by Lixiang Liu, Peng Li

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