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A Multi-objective Optimization Model for Sustainable-Robust Aggregate Production Planning Problem 1

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science, engineering Management and Information Technology First international conference, SEMIT 2022

作者： Tirkolaee, Erfan Babaee Aydın, Nadi Serhan Mahdavi, Iraj Çelik, Büşra Department of Industrial Engineering Istinye University Istanbul34396 Turkey Department of Industrial Engineering Mazandaran University of Science and Technology Babol Iran

ISBN: (数字)9783031403958

ISBN: (纸本)9783031403941

Aggregate production planning (APP) is known as a demand-driven production planning activity using aggregate plans for manufacturing processes. It tries to match supply and demand within a medium-term time horizon. In this work, a sustainable-robust APP problem is modeled through a multi-objective mixed-integer linear programming (MOMILP) model. The objective functions are formulated in a way to simultaneously minimize total cost, minimize total environmental impacts and maximize service level. Then, robust optimization (RO) technique is used to treat the demand uncertainty within the problem. To treat the multi-objectiveness and find the optimal solution, an improved multi-choice goal programing (IMCGP) method is introduced as an extension to the classical goal programming approach (GP). Next, several numerical examples are generated in different scales to assess the validity and applicability of the suggested methodology under deterministic as well as uncertain conditions. Eventually, a set of sensitivity analyses are implemented to assess the behavior of objective functions against real-world uncertainty in model parameters. It is demonstrated that the proposed methodology is capable of modeling, solving and analyzing the sustainable-robust APP problem efficiently. As one of the main findings, although the 1st and 2nd objective functions are sensitive to conservatism level, the 3rd objective function remains neutral. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Sensitivity analysis

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Tumor Infiltration of Microrobot using Magnetic torque and AI Technique 2

Tumor Infiltration of Microrobot using Magnetic torque and A...

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2nd IEEE international conference on Vision Towards Emerging Trends in Communication and Networking Technologies, ViTECoN 2023

作者： Shalini, R. Mishra, Laxmi Athulya, S. Chimankar, Abhijeet Gajanan Kandavalli, Sunanda Ratna. Keshav Kumar, K. Selvan, R. Senthamil School of Computing Sciences Vels Institute of Science Technology and Advanced Studies Department of BCA & IT Chennai India Khwaja Moinuddin Chishti Language University Department of Electronics and Communication Engineering Uttar Pradesh India Christ Deemed to Be University Faculty of Engineering Department of Computer Science and Engineering Bangalore India Chatrapati Shivaji BCA and BCS College Department of B.Sc. Computer Science Maharashtra India Sri Padmavati Mahila Visva Vidyalayam Department of Electronics and Communication Engineering Tirupati India G. Narayanamma Institute of Technology and Science Department of Humanities and Mathematics Hyderabad India Annamacharya Institute of Technology & Sciences Department of Electronics and Communication Engineering Tirupati India

ISBN: (纸本)9798350347982

Because of their surroundings and lifestyle alternatives, human beings, these days be afflicted by a huge style of illnesses. thus, early contamination prediction will become crucial. on the other hand, primarily based just on signs, docs warfare to make correct forecasts. The most challenging issue is accurately forecasting illnesses, which is why machine learning is essential to accomplish this task. To identify concealed patterns within vast amounts of medical data, disease information is processed using data mining techniques. We evolved a extensive contamination prediction primarily based on the affected person's signs. We rent the device getting to know techniques Convolutional Neural network (CNN) and ANFIS to exactly count on sickness (adaptive community-based totally fuzzy inference machine). For an correct forecast, this trendy illness prediction considers the character's way of life picks and fitness history. ANFIS outperforms CNN's set of rules in phrases of popular infection prediction, with an accuracy price of 96.7%. additionally, CNN consumes extra memory and processing energy than ANFIS because it trains and assessments on facts from the UCI repository. The Anaconda notebook is a suitable tool for implementing Python programming as it contains a range of libraries and header files that enhance the accuracy and precision of the process. © 2023 IEEE.

关键词： Forecasting

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A Nonlinear Interval programming Model based on Fuzzy Neural Networks 2

A Nonlinear Interval Programming Model based on Fuzzy Neural...

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2nd international conference on Distributed Computing and Optimization Techniques, ICDCOT 2024

作者： Zhu, Jijin Wu, Qinqin Luo, Chan College of Mechanical and Electrical Engineering Guangdong University of Science and Technology Dongguan China Mathematics Teaching and Research Office Dongguan Guangming Primary School Dongguan China

ISBN: (纸本)9798350382952

Compared to traditional deterministic problem research methods, interval analysis methods have a larger computational load and longer computational time due to the presence of uncertainty. Therefore, for models with complex structures or large scales, there is a lot of uncertain information, which requires a significant amount of computation and reduces the efficiency of the algorithm. The current optimization algorithms also have such shortcomings. In order to improve algorithm efficiency, this article focuses on researching parallel computing methods for interval optimization, designing efficient parallel algorithms, decomposing optimization problems into multiple subtasks that can be parallelized, and analyzing the feasibility and effectiveness of these algorithms in detail. The results indicate that multiple artificial neural network models are used to establish mapping relationships between design variables and uncertain variables, corresponding objective function values, and constraint function values. The objective function and each constraint function are trained with one network each, and a heuristic algorithm is selected as the inner and outer layer optimization solver. © 2024 IEEE.

关键词： Fuzzy neural networks

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IntelligentDine: Advanced Food Identification and Caloric Assessment through Deep Learning for Smart Diet Tracking 2

IntelligentDine: Advanced Food Identification and Caloric As...

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2nd IEEE international conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： Vaithiyanathan, M. Prasad, Ch. Krishna Lenka, Abhipsa Nayak, Sasmita Maniraj, P. Arigela, Arun Kumar Department of Information Technology Sri Sairam Engineering College Chennai India Department of Computer Science and Engineering Anurag Engineering College Telangana Kodad India Department of Electronics and Instrumentation Engineering Odisha University of Technology and Research Odisha Bhubaneswar India Department of Mechanical Engineering Government College of Engineering Kalahandi OdishaBhawani Patna India Department of Electrical and Electronics Engineering M.Kumarasamy College of Engineering Karur Thalavapalayam India Telangana Hyderabad India

ISBN: (纸本)9798350384277

The IntelligentDine initiative introduces an inventive approach to enhance diet tracking and promote healthy eating habits by applying advanced deep learning techniques. The primary goal is to precisely identify various food items and offer real-time estimates of their calorie content, providing users with intelligent and personalized diet monitoring capabilities. Using the Python programming language, we employed the ResNet150 architecture model for food recognition and calorie estimation, utilizing the extensive Food 101 dataset with 37,046 food images spanning 101 distinct food classes. Following rigorous training and evaluation, our model demonstrated notable success, achieving a training accuracy of 97.30% and a validation accuracy of 98.02%. These compelling results underscore the efficacy of our proposed approach in accurately recognizing and categorizing diverse food items. Smart Bite, a key component of this initiative, harnesses deep learning algorithms to swiftly analyze input images within a web framework, identifying specific food items and estimating their calorie content. This valuable information empowers users to effectively monitor their dietary *** intelligent diet monitoring capabilities of Smart Bite enable users to make informed decisions about their food choices. By tracking and analyzing daily food intake, users can gain insights into their nutritional habits, set personalized goals, and make necessary adjustments for a balanced and healthy diet. SmartBite showcases the successful integration of deep learning techniques, specifically employing the ResNet150 architecture for food recognition and calorie estimation. With its impressive accuracy, real-time processing capabilities, and intelligent diet monitoring features, SmartBite has the potential to transform how individuals track and manage their dietary habits, fostering healthier lifestyles. © 2024 IEEE.

关键词： Caloric Deep Learning Analysis food images real-time ResNet150

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Research on Gold Bitcoin Synthesis Algorithm Based on Particle Swarm Optimization and Dynamic programming 2

Research on Gold Bitcoin Synthesis Algorithm Based on Partic...

引用

2nd IEEE international conference on Data science and Computer Application, ICDSCA 2022

作者： Chen, Yang Liu, Zihao Cai, Shile Cui, Xinqi Hua, Jingyi College of Artificial Intelligence Nanjing Agricultural University Jiangsu Nanjing210031 China College of Engineering Nanjing Agricultural University Jiangsu Nanjing210031 China

ISBN: (数字)9781665472005

ISBN: (纸本)9781665472005

In this paper, we hope to study the transaction process of bitcoin and gold, two unstable assets, to find a trading model that can predict as accurately as possible and put forward a good algorithm. In the beginning, this paper predicted the future price movements of gold and bitcoin based on the long short-term memory neural network model. Then, based on the price of the day, this paper established a strategy model based on the Sharpe ratio and particle swarm algorithm. In order to better quantify the relationship between daily investment risks and returns, we introduced the Sharpe ratio and set the objective function to adjust the position and the value of the Sharpe ratio on the third day when the next three days are unchanged when the objective function is at the maximum value is the situation with the maximum risk and benefit. Finally, this paper established a comprehensive planning model for cash, gold, and Bitcoin through the dynamic programming process. A particle swarm algorithm simulated the optimization process, and the optimal solution was found. We obtained the Sharpe rate on the third day as the objective function. © 2022 IEEE.

关键词： Dynamic programming

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Trajectory Optimization of Multi-Pass Aeroassisted Orbital Transfer by Sequential Convex programming 2

Trajectory Optimization of Multi-Pass Aeroassisted Orbital T...

引用

2nd international conference on Mechanics, Electronics, Automation and Automatic Control, MEAAC 2024

作者： Feng, Xiangdong Han, Hongwei Chen, Jilin School of Aerospace Engineering Beijing Institute of Technology Beijing China

ISBN: (纸本)9781643685403

Aeroassisted transfer technology is that spacecraft utilizes aerodynamic forces generated during atmospheric flight to alter orbit dimensions or achieve changes in orbital inclination, which offers advantages in fuel cost. In this paper, a multi-pass aeroassisted orbit transfer scheme is proposed, with only deorbit and insertion maneuver impulse. On this basis, the optimal control problem of multi-pass is constructed with the bank angle as the control variable. The detailed derivation of the optimization problem with interior constraint and the endpoint constraint is given. After that, the non-linear problem is transformed into a convex problem, and a sequential convex optimization method is used to solve the optimal control problem numerically. Simulation show that the multi-pass aeroassist transfer has lower peak values of heating rate, dynamic pressure, and load factor. Compared to initial trajectories with constant bank angle, the scheme can save over 30% in fuel consumption. Â© 2024 The Authors.

关键词： Convex optimization

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Design of flexible clamping system of printing roller based on sliding mode control 2

Design of flexible clamping system of printing roller based ...

引用

2nd international conference on Computer science, Electronic Information engineering and Intelligent Control Technology, CEI 2022

作者： Cao, ShaoZhong Yang, QingXin Zhao, Wei Wang, HaiFei Beijing Institute of Graphic Communication Electronic Information Engineering Beijing China

ISBN: (数字)9781665476164

ISBN: (纸本)9781665476164

Manipulator is developed in the process of mechanization and automation of a new type of equipment, it is an important area of the industrial robot, its characteristic is that can be done by programming the default task, on the structure and properties of both human and mechanical advantage, in the modern industrial production process, the manipulator is widely used in automatic production line, now the factory a lot of the manipulator, In the flexibility may not be comparable to the real hand, but it is not afraid of fatigue, not afraid of danger, can be uninterrupted continuous work, can effectively improve industrial productivity, because of many advantages suitable for industrial production, manipulator has been widely used [1]. © 2022 IEEE.

关键词： Sliding mode control

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An Efficient Off-grid Express Cabinet Based on Wind-solar Hybrid Power Generation System 2

An Efficient Off-grid Express Cabinet Based on Wind-solar Hy...

引用

2nd international conference on Smart Energy, ICSE 2023

作者： Gu, Xiaosong Qu, Jiayi Yuan, Yongzhe Li, Le The School of Energy and Power Changsha University of Science and Technology Changsha410076 China The College of Aerospace Science and Engineering Science and Technology on Scramjet Laboratory National University of Defense Technology Changsha410073 China Xiaosong GU

In order to effectively solve the shortcomings of traditional express cabinets such as limited service places and seasonal power supply obstacles, this paper studies an off-grid express cabinet using wind-solar complementary principle, which is mainly composed of near-ground and low-speed wind power generation device, solar photovoltaic battery pack, controller, battery pack and DC load. The double-axis tracking solar panels or fixed photovoltaic panels can be used for different regions. At the same time, it can be combined with a near-ground and low-speed wind power generation device to provide a stable power supply for the express cabinets. By programming the control, the power generated by wind-solar hybrid power generation is provided to the load as a priority. The remaining electric energy is stored in the battery pack. The system effectively overcomes the disadvantages of limited-service locations and unstable power supply caused by seasonal barriers in traditional express cabinets. It has the advantages of energy-saving, environmental protection, short payback period, and wide range of supply. © Published under licence by IOP Publishing Ltd.

关键词： Energy conservation

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Smart IoT_Cloud-Based ML Technique to Classify Breast Cancer 2

Smart IoT_Cloud-Based ML Technique to Classify Breast Cancer

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2nd international conference on Ambient Intelligence in Health Care, ICAIHC 2023

作者： Prusty, Sashikanta Dash, Sujit Kumar Prusty, Sushree Gayatri Priyadarsini Dalai, Sasanka Sekhar Tripathy, Nrusingha Nayak, Subrat Kumar Department of Computer Science & Engineering Bhubaneswar751030 India Department of Electrical & Electronics Engineering Bhubaneswar751030 India

ISBN: (纸本)9798350344882

IoT and cloud computing have a significant impact on healthcare services, particularly when it comes to disease prediction in smart cities. Big data about breast cancer (BC) can be sent through IoT devices (digital sensors, etc.) and stored in the cloud. As a result, these huge data are used to improve BC prediction accuracy in a cloud setting. Thus, BC-based cloud IoT is thought to be a significant issue that smart city stakeholders in health care must deal with. In smart cities, cloud computing helps patients predict the presence of BC anywhere and at any time by using advanced machine learning (ML) techniques. The main goal of this study is to demonstrate the effectiveness of a secure Internet of Things and cloud computing in the identification of BC at our home. Thus, we proposed an ICM (IoT_Cloud-based ML) method that describes the workflow of how a user can predict BC disease at any place and at any time. And finally, we designed performance metrics for all three models and found logistic regression model (LR) outperforms with higher accuracy of 83% than DT at 72% and NB at 80%. However, all these experiments have been carried out using Python 3.8.3 programming software on the Jupyter 6.4.3 Notebook platform in Windows 10 operating system. © 2023 IEEE.

关键词： Cloud computing

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Streamlining Transfer Applications in Education: AI and Python-driven Mapping of Technological Proficiencies 2

Streamlining Transfer Applications in Education: AI and Pyth...

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2nd international conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023

作者： Krishnan, Sumathy Surendran, R. Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350325799

This software acknowledges and enhances the process of transferring between academic institutions, universities, courses in the same institution, and a handful of other possible potentials which can often be less precise and time-consuming more specifically for students when it's done manually. Henceforth, this research paper explores the use of artificial intelligence (AI) and Python programming in developing an online system that simplifies and enhances the transfer application process (TAP). By giving an accurate percentage of their chances of getting into the desired institution on their desired course. Leveraging all techniques, such as natural language processing, this system aims to streamline the application process, provide personalized guidance, and improve the overall quality of transfer application software (TAS). This paper discusses the various components of the system, including data collection, processing, analysis, and user interface design. Furthermore, this paper highlights the potential benefits, challenges, and ethical considerations associated with the integration of AI and Python in the transfer application process (TAP). However, advancements in artificial intelligence (AI) and the utilization of Python online have paved the way for innovative solutions that can simplify and enhance the transfer application process. This research paper explores the use of AI and Python online to streamline transfer applications (STA), making them more accessible and ensuring the submission of high-quality applications. Through the integration of All-powered algorithms and Python-based tools like Django, this paper demonstrates how the transfer application process can be optimized, resulting in improved efficiency, accuracy, and user-friendly experience. © 2023 IEEE.

关键词： Python

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