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2015 International Conference on Computer Science and Environmental Engineering(CSEE 2015)

作者： Z.Li Y.P.Yang Department of Automotive Engineering Traffic InstituteInner Mongolia University School of Automobile Chang'an University

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.

关键词： logistics nodes logistics network spatial model optimizing algorithm

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An LSTM-based optimization algorithm for enhancing quantitative arbitrage trading

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PEERJ COMPUTER SCIENCE 2024年 10卷 e2164页

作者： Han, Guodong Li, Hecheng Qinghai Normal Univ Coll Comp Xining Peoples R China Bank Qinghai Digital Finance Dept Xining Peoples R China Qinghai Normal Univ Sch Math & Stat Xining Peoples R China

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.

关键词： LSTM model Arbitrage trading optimizing algorithm

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Evaluation of Optimization algorithms for Measurement of Suspended Solids

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WATER 2024年第13期16卷 1761-1761页

作者： Lopez-Betancur, Daniela Gonzalez-Ramirez, Efren Guerrero-Mendez, Carlos Saucedo-Anaya, Tonatiuh Rivera, Martin Montes Olmos-Trujillo, Edith Jimenez, Salvador Gomez Univ Autonoma Zacatecas Unidad Acad Ciencia & Tecnol Luz & Mat Parque Ciencia & Tecnol QUANTUM Ciudad Conocimient Zacatecas 98160 Mexico Univ Autonoma Zacatecas Unidad Acad Ingn Electr Campus Univ UAZ Siglo XXIEdificio E14 Zacatecas 98160 Mexico Univ Autonoma Zacatecas Unidad Acad Ingn 1 Av Ramon Lopez Velarde 801 Zacatecas 98000 Mexico

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.

关键词： optimizing algorithm loss function minimal local turbidity

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A Nurse Reallocation method for successful change management during Electronic Health Record systems implementations 23

A Nurse Reallocation method for successful change management...

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Proceedings of the 27th Pan-Hellenic Conference on Progress in Computing and Informatics

作者： Fotios Panagiotopoulos Leonidas Fragidis Vassilios Chatzis Department of Management Science and Technology International Hellenic University Greece

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.

关键词： E-health innovations Electronic Health Record Human resource allocation optimizing algorithm Resistance to change

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Parameter Identification and State-of-Charge Estimation for Li-Ion Batteries Using an Improved Tree Seed algorithm

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2019年第8期E102D卷 1489-1497页

作者： Chen, Weijie Cai, Ming Tan, Xiaojun Wei, Bo Sun Yat Sen Univ Sch Intelligent Syst Engn Guangzhou Guangdong Peoples R China Waseda Univ Grad Sch Fundamental Sci & Engn Tokyo 1698555 Japan

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.

关键词： parameter identification optimizing algorithm tree seed algorithm differential evolution swarm intelligence

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EDN: An Efficient Educational Network for optimizing Education Resources

EDN: An Efficient Educational Network for Optimizing Educati...

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2019 IEEE International Conference on Computer Science and Educational Informatization, CSEI 2019

作者： Nauman, Umer Zhang, Yuhong Information Science and Engineering College Henan University of Technology Zhengzhou China School of Information and Software Engineering University of Electronic Science and Technology of China Chendu China

ISBN: (纸本)9781728123080

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. © 2019 IEEE.

关键词： educational network equity in educational resources optimizing algorithm

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EDN : An Efficient Educational Network for optimizing Education Resources

EDN : An Efficient Educational Network for Optimizing Educat...

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第一届计算机科学与教育信息化国际会议

作者： Umer Nauman Yuhong Zhang Information Science and Engineering College Henan University of Technology School of Information and Software Engineering University of Electronic Science and Technology of China

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.

关键词： educational network equity in educational resources optimizing algorithm

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Rearch on Winning Decision's optimizing algorithm for Combinatorial Bidding Purchase of Service in the Supply Chain

Rearch on Winning Decision's Optimizing Algorithm for Combin...

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International Conference on Building Materials and Structural Engineering (BMSE 2012)

作者： Ma, Jinlin Qian, Lijuan Liu, Zhiqiang Jiangsu Univ Sch Automobile & Traff Engn Zhenjiang Jiangsu Peoples R China Jiangsu Univ Fac Sci Zhenjiang Jiangsu Peoples R China

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.

关键词： combinatorial purchase service supply chain winning decision optimizing algorithm

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Application of optimization algorithms for robot systems designing

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INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 2018年第1期15卷

作者： Sapietova, Alzbeta Saga, Milan Kuric, Ivan Vaclav, Stefan Univ Zilina Dept Appl Mech Fac Mech Engn Univ 1 SK-01026 Zilina Slovakia Univ Zilina Dept Automat & Prod Syst Fac Mech Engn Zilina Slovakia Slovak Univ Technol Inst Prod Technol Fac Mat Sci & Technol Trnava Slovakia

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

关键词： Kinematics of robotic system optimizing algorithm coupled mechanical systems MATLAB

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An optimizing pipeline stall reduction algorithm for power and performance on multi-core CPUs

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HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES 2015年第1期5卷 1-13页

作者： Saravanan, Vijayalakshmi Pralhaddas, Kothari Dwarkadas Kothari, Dwarkadas Pralhaddas Woungang, Isaac Ryerson Univ WINCORE Lab Toronto ON Canada IIT Delhi India

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.

关键词： Instruction pipeline Stall reduction optimizing algorithm

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