In the rapid development of the city,negative problems also created in the *** can't be ignored of the increasingly serious traffic *** urban freight logistics is the only way to solve the *** researches about cit...
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In the rapid development of the city,negative problems also created in the *** can't be ignored of the increasingly serious traffic *** urban freight logistics is the only way to solve the *** researches about city logistics nodes are *** the sales logistics distribution network,this paper proposes a city nodes spatial *** sales logistics distribution network is divided into two modes,production transform and twice different distribution *** mode has universal and typical *** on the established mode,the optimizing algorithm of the twice different distribution types is put forward and described.
Arbitrage trading is a common quantitative trading strategy that leverages the longterm cointegration relationships between multiple related assets to conduct spread trading for profit. Specifically, when the cointegr...
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Arbitrage trading is a common quantitative trading strategy that leverages the longterm cointegration relationships between multiple related assets to conduct spread trading for profit. Specifically, when the cointegration relationship between two or more related series holds, it utilizes the stability and mean-reverting characteristics of their cointegration relationship for spread trading. However, in real quantitative trading, determining the cointegration relationship based on the Engle-Granger twostep method imposes stringent conditions for the cointegration to hold, which can easily be disrupted by price fluctuations or trend characteristics presented by the linear combination, leading to the failure of the arbitrage strategy and significant losses. To address this issue, this article proposes an optimized strategy based on long-short-term memory (LSTM), termed Dynamic-LSTM Arb (DLA), which can classify the trend movements of linear combinations between multiple assets. It assists the Engle-Granger two-step method in determining cointegration relationships when clear upward or downward non-stationary trend characteristics emerge, avoiding frequent strategy switches that lead to losses and the invalidation of arbitrage strategies due to obvious trend characteristics. Additionally, in meanreversion arbitrage trading, to determine the optimal trading boundary, we have designed an optimized algorithm that dynamically updates the trading boundaries. Training results indicate that our proposed optimization model can successfully filter out unprofitable trades. Through trading tests on a backtesting platform, a theoretical return of 23% was achieved over a 10-day futures trading period at a 1-min level, significantly outperforming the benchmark strategy and the returns of the CSI 300 Index during the same period.
Advances in convolutional neural networks (CNNs) provide novel and alternative solutions for water quality management. This paper evaluates state-of-the-art optimization strategies available in PyTorch to date using A...
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Advances in convolutional neural networks (CNNs) provide novel and alternative solutions for water quality management. This paper evaluates state-of-the-art optimization strategies available in PyTorch to date using AlexNet, a simple yet powerful CNN model. We assessed twelve optimization algorithms: Adadelta, Adagrad, Adam, AdamW, Adamax, ASGD, LBFGS, NAdam, RAdam, RMSprop, Rprop, and SGD under default conditions. The AlexNet model, pre-trained and coupled with a Multiple Linear Regression (MLR) model, was used to estimate the quantity black pixels (suspended solids) randomly distributed on a white background image, representing total suspended solids in liquid samples. Simulated images were used instead of real samples to maintain a controlled environment and eliminate variables that could introduce noise and optical aberrations, ensuring a more precise evaluation of the optimization algorithms. The performance of the CNN was evaluated using the accuracy, precision, recall, specificity, and F_Score metrics. Meanwhile, MLR was evaluated with the coefficient of determination (R2), mean absolute and mean square errors. The results indicate that the top five optimizers are Adagrad, Rprop, Adamax, SGD, and ASGD, with accuracy rates of 100% for each optimizer, and R2 values of 0.996, 0.959, 0.971, 0.966, and 0.966, respectively. Instead, the three worst performing optimizers were Adam, AdamW, and NAdam with accuracy rates of 22.2%, 11.1% and 11.1%, and R2 values of 0.000, 0.148, and 0.000, respectively. These findings demonstrate the significant impact of optimization algorithms on CNN performance and provide valuable insights for selecting suitable optimizers to water quality assessment, filling existing gaps in the literature. This motivates further research to test the best optimizer models using real data to validate the findings and enhance their practical applicability, explaining how the optimizers can be used with real data.
In recent years, most hospitals worldwide are trying to implement systems regarding the Electronic Health Record (EHR). The EHR systems are part of wider information systems used in healthcare. In EHR implementation i...
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ISBN:
(纸本)9798400716263
In recent years, most hospitals worldwide are trying to implement systems regarding the Electronic Health Record (EHR). The EHR systems are part of wider information systems used in healthcare. In EHR implementation in hospitals, nurses’ resistance to change is considered as one of the most important factor for adoption or failure of the digital technologies application. Researchers have proposed several alternative strategies for successful implementation of EHR, which focus to reduce the nurses’ resistance. This paper proposes an innovative approach to the management of nurses’ resistance during the change process of the EHR implementation. The development of information systems has provided us with direct access to information and data that may be used for the successful implementation of changes, which typically rely on controlling the employees’ inherent resistance to change. More specifically, during implementation the nurses’ allocation should be adjusted at an appropriate time, which is found by the proposed monitoring and Nurse Reallocation (NuRe) method.
Accurate estimation of the state-of-charge is a crucial need for the battery, which is the most important power source in electric vehicles. To achieve better estimation result, an accurate battery model with optimum ...
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Accurate estimation of the state-of-charge is a crucial need for the battery, which is the most important power source in electric vehicles. To achieve better estimation result, an accurate battery model with optimum parameters is required. In this paper, a gradient-free optimization technique, namely tree seed algorithm (TSA), is utilized to identify specific parameters of the battery model. In order to strengthen the search ability of TSA and obtain more quality results, the original algorithm is improved. On one hand, the DE/rand/2/bin mechanism is employed to maintain the colony diversity, by generating mutant individuals in each time step. On the other hand, the control parameter in the algorithm is adaptively updated during the searching process, to achieve a better balance between the exploitation and exploration capabilities. The battery state-of-charge can be estimated simultaneously by regarding it as one of the parameters. Experiments under different dynamic profiles show that the proposed method can provide reliable and accurate estimation results. The performance of conventional algorithms, such as genetic algorithm and extended Kalman filter, are also compared to demonstrate the superiority of the proposed method in terms of accuracy and robustness.
In Pakistan, education resource imbalance is a serious social problem that needs to be solved urgently. Educational network (EDN) is an efficient technological means which can solve the above problems efficiently. In ...
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In Pakistan, education resource imbalance is a serious social problem that needs to be solved urgently. Educational network(EDN) is an efficient technological means which can solve the above problems efficiently. In t...
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In Pakistan, education resource imbalance is a serious social problem that needs to be solved urgently. Educational network(EDN) is an efficient technological means which can solve the above problems efficiently. In this paper, we first analyze the status quo of Pakistan. Then we further discussed how we developed an EDN for the department of computer science based in the University of Peshawar, Pakistan. In EDN,We emphasize data security and data integrity, which are the primary concerns for us. Our Feedback shows that the coverage and utilization efficiency of high-quality education resources have achieved dramatic improvements after the adoption of EDN.
For the actual requirements of combinatorial purchase of service in the supply chain, the process of Euclidean distance is presented in this paper to solve the winning decision problem. The method uses mixed set progr...
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ISBN:
(纸本)9783037853603
For the actual requirements of combinatorial purchase of service in the supply chain, the process of Euclidean distance is presented in this paper to solve the winning decision problem. The method uses mixed set programming to describe all the relations and constraints in the decentralized object programming models which are different in orientation and dimension. The optimizing algorithm is designed and iterated for minimum distance to find the satisfactory solution. A numerical example confirms the validity and practicability of the algorithm.
The article presents the design and application of multi-software platform for solving kinematic synthesis of robot manipulator systems. It also presents a modern theoretical and application approach for modelling cou...
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The article presents the design and application of multi-software platform for solving kinematic synthesis of robot manipulator systems. It also presents a modern theoretical and application approach for modelling coupled mechanical systems, which include mobile robots. Due to high requirements for accuracy, efficiency, reliability and life cycle of technical equipment, several parameters ensuring optimal operating parameters need to be taken into account while dealing with the design. This is the reason for linking computational models to optimization algorithms that allows us to find the appropriate design parameters of analysed mechanical system, mechanisms, including mobile robots mostly by iterative way. The commercial working interface of the program ADAMS and open architecture of MATLAB programming language enable to share common data while dealing with model simulations in parallel. Both of them were used while designing and implementing the algorithm for the evaluation and optimization of parameters of technical equipment from the point of view of selected properties. While working on the task of the spatial mechanism of the six-member robot manipulator system, the algorithm solving the optimal parameters was created by applying the selected optimization techniques of the program MATLAB. Presented algorithm involves the creation of a map operating positions, which is further linked to the solution of the motion of interest points in the robotic system following a prescribed trajectory. This requires the geometry optimization of the selected members of the spatial robotic system in order to achieve such parameters so that the trajectory of the interest point of the output member would precisely match with the prescribed trajectory. It is important to note that these types of tasks create wider space for solving the assignments dealing with the development and application of technical equipment like mobile robots and their outputs that are linked to the needs
The power-performance trade-off is one of the major considerations in micro-architecture design. Pipelined architecture has brought a radical change in the design to capitalize on the parallel operation of various fun...
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The power-performance trade-off is one of the major considerations in micro-architecture design. Pipelined architecture has brought a radical change in the design to capitalize on the parallel operation of various functional blocks involved in the instruction execution process, which is widely used in all modern processors. Pipeline introduces the instruction level parallelism (ILP) because of the potential overlap of instructions, and it does have drawbacks in the form of hazards, which is a result of data dependencies and resource conflicts. To overcome these hazards, stalls were introduced, which are basically delayed execution of instructions to diffuse the problematic situation. Out-of-order (OOO) execution is a ramification of the stall approach since it executes the instruction in an order governed by the availability of the input data rather than by their original order in the program. This paper presents a new algorithm called Left-Right (LR) for reducing stalls in pipelined processors. This algorithm is built by combining the traditional in-order and the out-of-order (OOO) instruction execution, resulting in the best of both approaches. As instruction input, we take the Tomasulo's algorithm for scheduling out-of-order and the in-order instruction execution and we compare the proposed algorithm's efficiency against both in terms of power-performance gain. Experimental simulations are conducted using Sim-Panalyzer, an instruction level simulator, showing that our proposed algorithm optimizes the power-performance with an effective increase of 30% in terms of energy consumption benefits compared to the Tomasulo's algorithm and 3% compared to the in-order algorithm.
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