Proposed Method for Note Detection and Automatic Identification of the Melody Models (Gusheh) in Iranian Traditional Music with Micro Approach by Amir Vafaeian, Keivan Borna, Hamed Sajedi, Dariush Alimohammadi, Pouya Sarai

“…Finally, the optimization problem is solved via greedy and dynamic programming approaches and while selecting the best sentences, the final summary is generated. …”
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Comparison of different models for energy management strategy design of a parallel hybrid electric vehicle: Impact of the rotating masses by Abdoulaye Pam, Alain Bouscayrol, Philippe Fiani, Fabien Faval

“…Moreover, optimal algorithms such as dynamic programming (DP) are used off‐line to define a benchmark for real‐time EMSs. …”
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Deep Learning-Based Home Energy Management Incorporating Vehicle-to-Home and Home-to-Vehicle Technologies for Renewable Integration by Marwan Mahmoud, Sami Ben Slama

“…By utilizing data from a Tunisian weather database, smart cities significantly reduce electricity costs compared to traditional energy management methods, such as Dynamic Programming (DP), Rule-Based Systems, and Genetic Algorithms. …”
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Comprehensive Research on Energy Saving Synergy Optimization and Optimal Real-time Control of Hybrid Electric Mining Trucks by Li Hongliang, Zhang Guojing, Fan Ping

“…This study takes the hybrid electric mining truck as a research object, establishes the mathematical model of the whole vehicle, takes reducing fuel consumption as the goal, establishes a collaborative optimization model that comprehensively considers the interaction between transmission system parameters and energy management strategies, and combines particle swarm optimization (PSO) algorithm and dynamic programming (DP) algorithm to build a two-layer interactive optimization algorithm to eliminate the interaction between transmission system parameters and energy management strategies. …”
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Towards Fault Detection in Industrial Equipment through Energy Consumption Analysis: Integrating Machine Learning and Statistical Methods by Baddou Nada, Dadda Afaf, Rzine Bouchra, Hmamed Hala

“…The second part of the model, which focuses on detecting change points in consumption patterns, was evaluated by testing several cost functions combined with binary segmentation and dynamic programming. Applied to a real-world case, it successfully detected a change point two months before equipment failure, offering the potential to reduce energy consumption by 27,052 kWh. …”
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Energy Management Strategies for Extended-Range Electric Vehicles with Real Driving Emission Constraints by Hualong Xu, Yang Chen, Li Zhang, Guoliang Chen, Jinlin Han, Qing Zhang, Chaokai Li

“…The optimization problem is solved using a dynamic programming (DP) algorithm embodying the interpolated-startup-corrected emission models, and the start–stop reduction strategies and condition migration strategies are derived. …”
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Air Traffic Efficiency Analysis of Airliner Scheduled Flights Using Collaborative Actions for Renovation of Air Traffic Systems Open Data by Akinori Harada, Tooru Ezaki, Tomoaki Wakayama, Koichi Oka

“…Each reconstructed trajectory is optimized in terms of flight fuel consumption and flight time with an assumed cost index (CI). Dynamic programming is used as the trajectory optimization method. …”
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The Value of Preemptive Pick-Up Services in Dynamic Vehicle Routing for Last-Mile Delivery: Space-Time Network-Based Formulation and Solution Algorithms by Weiran Meng, Lingyun Meng, Guoshuai Han, Xiaotian Zhuang, Lu Carol Tong, Shengnan Wu

“…To provide a fast value approximation, we present a solution framework deploying the augmented Lagrangian relaxation approach with embedded dynamic programming algorithms. This framework jointly integrates the processes of updating request information and obtaining optimal routes. …”
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Deep Q-Networks for Minimizing Total Tardiness on a Single Machine by Kuan Wei Huang, Bertrand M. T. Lin

“…Due to its computational intractability, exact approaches such as dynamic programming algorithms and branch-and-bound algorithms struggle to produce optimal solutions for large-scale instances in a reasonable time. …”
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Optimization of spline parameters in approximation of multivalued functions by D. A. Karpov, V. I. Struchenkov

“…The first stage of this work consisted in determining the number of elements of the approximating spline using dynamic programming. In the present paper, the next stage of solving this problem is carried out.Methods. …”
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Multi-Temporal Energy Management Strategy for Fuel Cell Ships Considering Power Source Lifespan Decay Synergy by Xingwei Zhou, Xiangguo Yang, Mengni Zhou, Lin Liu, Song Niu, Chaobin Zhou, Yufan Wang

“…The overall performance of this strategy approaches the global optimal solution obtained through Dynamic Programming, comprehensively validating its superiority in simultaneously optimizing system economics and durability.…”
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Multilayer entropy-weighted TOPSIS method and its decision-making in ecological operation during the subsidence period of the Three Gorges Reservoir by Ai Xueshan, Yu Yangxin, Liang Zhiming, Shi Xuanyu, Cao Rui, Zhang Xiaoke

“…A multi-objective optimal reservoir scheduling model was constructed to coordinate the spawning flow demand of " Four Major Chinese Carps"; The model takes the maximum power generation and the maximum membership degree of downstream river ecological water demand as the objective functions, and uses the dynamic programming multi-objective solution algorithm based on penalty factors to solve the problem, and obtains the non-inferior solution set in each scenario. …”
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Research on network risk assessment based on attack graph of expected benefits-rate by Wenfu LIU, Jianmin PANG, Xin ZHOU, Nan LI, Feng YUE

“…As Internet applications and services become more and more extensive, the endless network attacks lead to great risks and challenges to the security of information systems.As a model-based network security risk analysis technology, attack graph is helpful to find the vulnerability between network nodes and the harm of being attacked.It has been proved to be an effective method to find and prevent network security risks.Attack graph is mainly divided into state-based attack graph and attribute-based attack graph.Due to the problem of state explosion in state-based attack graph, most researchers prefer the attribute-based attack graph for network risk assessment.In view of the existing researches on attribute-based attack graph, they excessively rely on the vulnerability of network nodes and the essential attributes of atomic attack.However, they ignore that rational attackers usually choose specific attack paths by maximizing attack benefits.Then, a network risk assessment framework and a quantification method of attack benefits-rate based on expected benefits-rate attack graph were proposed.The network risk assessment framework took the open vulnerability resource database, the new vulnerabilities found by the vulnerability mining system and the big data related to network attack and defense as the basic data source.The network risk assessment framework also took the open source big data platform as the analysis tool to mine and calculate the elements related to attack cost and attack benefit.Using the concepts of cost, benefit and benefit-rate in economics, the calculation model of expected benefit-rate of atomic attack was constructed.By constructing the attribute-based attack graph of the target network, the expected benefit-rate of atomic attack on the attack path was calculated, and the expected benefit-rate list of all possible attack paths was generated.Furthermore, taking the expected goal as the starting point, the search was carried out according to the specific optimization strategy (backtracking method, greedy algorithm, dynamic programming).And the complete attack path with the maximum benefit-rate was obtained, which provided the basis for network risk assessment.The simulation results show the effectiveness and rationality of the proposed expected benefit-rate attack graph network risk assessment method, which can provide support for discovering and preventing network security problems.…”
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Q-learning global path planning for UAV navigation with pondered priorities by Kevin B. de Carvalho, Hiago de O.B. Batista, Leonardo A. Fagundes-Junior, Iure Rosa L. de Oliveira, Alexandre S. Brandão

“…Traditional techniques, including geometric and dynamic programming, have historically been employed to address this challenge. …”
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Enhanced vehicle routing for medical waste management via hybrid deep reinforcement learning and optimization algorithms by Norhan Khallaf, Osama Abd-El Rouf, Abeer D. Algarni, Mohy Hadhoud, Ahmed Kafafy

“…This led to the application of Fractional Knapsack dynamic programming with Deep Q Network to maximize capacity utilization while achieving optimal routes. …”
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Prior Knowledge-Based Two-Layer Energy Management Strategy for Fuel Cell Ship Hybrid Power System by Lin Liu, Xiangguo Yang, Xin Li, Xingwei Zhou, Yufan Wang, Telu Tang, Qijia Song, Yifan Liu

“…In the first layer of the EMS, which operates offline, dynamic programming (DP) and low-pass filtering (LPF) are used to allocate power optimally for different typical ship operating conditions. …”
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Business targeting in Iran: a hybrid simulation-optimization approach by amir mansour tehranchian, Sogand Hoseinnia Chafjiri

“…For this purpose, a policymaker's welfare loss function of linear quadratic and inter-period type including the deviation of inflation rate and economic growth from their targeted and approved values ​​in the country's sixth plan of economic, social and cultural development, with regard to the system of dynamic and non-linear equations of Keynesian macrometrics, is minimized by stochastic dynamic programming method. The system of dynamic and stochastic macrometric equations includes behavioral equations and defining equations. …”
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On a system of Hamilton-Jacobi-Bellman inequalities associated to a minimax problem with additive final cost by Silvia C. Di Marco, Roberto L. V. González

“…After introducing an auxiliary problem, we analyze the dynamical programming principle (DPP) and we present a Hamilton-Jacobi-Bellman (HJB) system. …”
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Research on data encryption system and technology for cloud storage by Peiyi HAN, Chuanyi LIU, Jiahui WANG, Shaoming DUAN, Hezhong PAN, Binxing FANG

“…To order to address the problem of cloud storage data security,the generic proxy-based data protection system was proposed,which could automatically and transparently secure sensitive data in browser-based cloud storage applications.A novel dynamic program analysis technique was adopted based on JavaScript API function hooking for automatically extending to various cloud applications.And a novel proxy executed searchable encryption solution was presented so that it could achieve data encryption while maintaining the original functions of cloud applications.Experimental results show that the system can support a variety of typical cloud services,effectively protect sensitive data,and bring a relatively low overhead.…”
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Delay-optimal spectrum decision method for cognitive network by Wu-jian SUN, Na LI, Yang LIU, Le SUN, Tao CHEN, Hao LI, Ou LI

“…Spectrum decision was investigated within the confine of spectrum management framework for cognitive radio networks.Sensing errors in PHY layer,outage probability on wireless channel and multiple interruptions of primary user were taken into consideration.Probability-based and sensing-based spectrum decision methods were proposed,which were capable of balancing traffic evenly among licensed.For the probability-based method,short-time first discipline was employed to further shorten average residual time,closed-formed expression were presented based on dynamical programing.For the sensing based method,new channel could be chosen for uncompleted transmission,which alleviated the time spent in waiting primary user.Optimal residual time was obtained by choosing the minimal value of the two methods.Furthermore,spectrum heterogeneity was taken into consideration and theoretical analysis was of general sense.Simulation results validate the approach is efficient.…”
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