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An artificial hummingbird algorithm based localization with reduced number of reference nodes for wireless sensor networks

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PHYSICAL COMMUNICATION 2022年 55卷

作者： Bhat, Soumya J. Santhosh, K. V. Manipal Acad Higher Educ MAHE Manipal Inst Technol Ctr Cyber Phys Syst Dept Instrumentat & Control Engn Manipal 576104 Karnataka India Shri Madhwa Vadiraja Inst Technol & Management Dept Comp Sci & Engn Bantakal 574115 Karnataka India

Wireless Sensor Networks (WSN) are widely used in recent years due to the advancements in wireless and sensor technologies. Many of these applications require to know the location information of nodes. This information is useful to understand the collected data and to act on them. Existing localization algorithms make use of a few reference nodes for estimating the locations of sensor nodes. But, the positioning and utilization of reference nodes increase the cost and complexity of the network. To reduce the dependency on reference nodes, in this paper, we have developed a novel optimization based localization method using only two reference nodes for the localization of the entire network. This is achieved by reference nodes identifying a few more nodes as reference nodes by the analysis of the connectivity information. The sensor nodes then use the reference nodes to identify their locations in a distributive manner using Artificial Hummingbird algorithm (AHA). We have observed that the localization performance of the reported algorithm at a lower reference node ratio is comparable with other algorithms at higher reference node ratios. (c) 2022 Elsevier B.V. All rights reserved.

关键词： Artificial hummingbird algorithm Hop based localization optimization algorithm Range free Reference nodes Wireless sensor network

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Self-Organizing Migrating algorithm with narrowing search space strategy for robot path planning

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APPLIED SOFT COMPUTING 2022年 116卷 108270-108270页

作者： Diep, Quoc Bao Truong, Thanh Cong Das, Swagatam Zelinka, Ivan VSB Tech Univ Ostrava Fac Elect Engn & Comp Sci Ostrava Czech Republic Univ Finance Mkt Ho Chi Minh City Vietnam Indian Stat Inst Elect & Commun Sci Unit Kolkata India Ton Duc Thang Univ Fac Elect & Elect Engn Ho Chi Minh City Vietnam

This article introduces a version of the Self-Organizing Migrating algorithm with a narrowing search space strategy named iSOMA. Compared to the previous two versions, SOMA T3A and Pareto that ranked 3rd and 5th respectively in the IEEE CEC (Congress on Evolutionary Computation) 2019 competition, the iSOMA is equipped with more advanced features with notable improvements including applying jumps in the order, immediate update, narrowing the search space instead of searching on the intersecting edges of hyperplanes, and the partial replacement of individuals in the population when the global best improved no further. Moreover, the proposed algorithm is organized into processes named initialization, self-organizing, migrating, and replacement. We tested the performance of this new version by using three benchmark test suites of IEEE CEC 2013, 2015, and 2017, which, together contain a total of 73 functions. Not only is it superior in performance to other SOMAs, but iSOMA also yields promising results against the representatives of well-known algorithmic families such as Differential Evolution and Particle Swarm optimization. Moreover, we demonstrate the application of iSOMA for path planning of a drone, while avoiding static obstacles and catching the target. (C) 2021 The Author(s). Published by Elsevier B.V.

关键词： Self-Organizing Migrating algorithm optimization algorithm Swarm intelligence Numerical optimization Path planning Drone

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Comprehensive exploration: Automatic mode-locking technology and its multidisciplinary applications

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INFRARED PHYSICS & TECHNOLOGY 2024年 138卷

作者： Liu, He Sun, Chenxi Zhang, Haoran Harbin Univ Sci & Technol Sch Measurement & Commun Engn Harbin Peoples R China

We present a thorough review of the evolution and current status of automatic mode -locking technology, offering insights into its remarkable developments. Automatic mode -locking technology commences with traversal algorithms and genetic algorithms, progressing to machine learning. The advancements of optimization algorithms have ushered in a new era characterized by exceptional time efficiency, enhanced precision, adaptability to multiple variables, and the ability to engage with complex mode -locking regimes. This review concentrates on the improvements of hardware components of automatic mode -locking technology in addition to these algorithmic advances. We introduce the evolution of pivotal components, including polarization control elements and central control sections, which play a critical role in achieving stability and integration, and introduction of realtime measurement techniques in hardware, such as the time -stretched dispersive Fourier transform, which accurate monitoring and adjustment of clamping status and optical characteristics. Finally, a summary and outlook on the development of automatic mode -locking technology is presented.

关键词： Automatic mode -locking optimization algorithm Time -stretched dispersive Fourier transform

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Traffic Management using Logistic Regression with Fuzzy Logic

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Procedia Computer Science 2018年 132卷 451-460页

作者： Anurag Singh Tomar Mridula Singh Girish Sharma K.V. Arya School of Computer Science University of Petroleum and Energy Studies Dehradun India Department of Computer Science Engineering Uttarakhand Technical University Dehradun India Department of Electronics and Telecommunication College of engineering Roorkee India Department of Master of Computer Application Bhai Parmanand Institute of Business Studies Shakarpur New Delhi India Department of Computer Science Engineering Institute of Engineering and Technology Lucknow India

Traffic congestion is one of the major problems in most of the cities across the globe and it leads to several other problems like pollution, time wastage, long traffic queues on roads and may cause accidents. Improvement of Road infrastructure is not always the feasible solution to resolve the problem. In real life scenario shorter distance route towards the destination attracts majority of people and at times it may aggravate traffic jam conditions. Therefore, a real time traffic information for intelligent decision making to decide the route preference is required. Moreover, a system which considers the factor of distance towards the destination along with real time traffic situation on that route will add to the solution to the congestion problem. certain parameters such as distance, weather condition, road location, day of week and time are considered to formulate the problem and to find solutions to these problems This paper outlines a combination of logistic regression with fuzzy logic such that a smart decision to preferred path can be taken. It is used to compute the probability of each possible path by considering the real time traffic information, distance and road condition and later is used to take decisions in an uncertain scenario. Proposed Method considers the number of parameters like distance, weather condition, road location, day of week and time.

关键词： Logistic regression Traffic management congestion fuzzy logic optimization algorithm fuzzy controller

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Optimizing Urban Electric Vehicle Charging Infrastructure Selection: An Approach Integrating GPS Data, Battery Levels, and Energy Availability

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IFAC-PapersOnLine 2024年第13期58卷 392-397页

作者： Meriem Belaid Said El Beid Anas Hatim CISIEV Team Cadi Ayyad University Marrakech 40160 Morocco TIM team Cadi Ayyad University Marrakech 40160 Morocco

This research paper offers a comprehensive exploration of how to enhance the charging infrastructure for Electric Vehicles (EVs) in urban settings. The analysis assesses three hypothetical charging infrastructures in a city, each with generators connected to the national grid and strategically placed AC and DC chargers. The proposed method employs GPS data, EV battery levels, and energy availability across the charging infrastructures. Using an optimization algorithm implemented via the Pandapower Python library, the most appropriate charging infrastructure is identified for individual drivers. The algorithm considers factors such as GPS data and energy availability to suggest the optimal charging station for each EV’s battery level. This pioneering solution aims to streamline the charging process, enhance user experience, and encourage efficient use of urban charging infrastructure for electric vehicles.

关键词： Electric Vehicle (EV) Charging Infrastructure Urban Environments AC Chargers DC Chargers GPS Data Battery Levels optimization algorithm Pandapower Python Library Sustainable Transportation User Experience

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Theoretical and experimental analyses and optimizations of direct coupling photovoltaic-thermoelectric systems

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ENERGY 2024年 307卷

作者： Xiong, Bowen Zhang, Jiayao Liao, Tianjun Zhao, Ye He, Zhihui Yang, Zhimin Yanan Univ Sch Phys & Elect Informat Yanan 716000 Peoples R China Chongqing Univ Technol Dept Phys & Energy Chongqing 400054 Peoples R China

A photovoltaic-thermoelectric (PV-TE) system is modeled theoretically and demonstrated experimentally. Mathematical formulations of the system are proposed according to energy conservation and finite-time thermodynamics, which can be applicable to analyze and optimize the system that consists of commercial photovoltaic (PV) cells and thermoelectric generators (TEGs). The genetic algorithm is introduced to maximize the system's power by optimizing multiple parameters. In Yan'an City, which is located in the northern Shaanxi Province in northwest China, the actual solar irradiance is recorded for almost a full year and the proposed model is verified. Theoretical and experimental results are analyzed and compared. It is found that there are several independent structure parameters in the PV-TE systems and they should be optimized simultaneously to maximize the performance. The PV-TE system's maximum theoretical average power of 0.343 W is 2.69 % greater than the solo PV cell's maximum theoretical power of 0.334 W. The measured average power of the system of 0.317 W is 0.32 % more than that of a solo PV cell of 0.316 W. The duration of strong lighting in Yan'an City reaches 8 h every day for nearly one year and the irradiation intensity can approach 1000 W/m2. The solar radiance is weakly affected by the seasonal changes of four seasons but is greatly affected by rainy days and cloud thickness. The research findings can serve as a helpful guide for the specific implementation of the PV-TE system and exploitation of solar energy resources in northwest China.

关键词： Photovoltaic-thermoelectric system Theoretical analysis Experimental validation Northwest China optimization algorithm

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An intelligent controller of homo-structured chaotic systems under noisy conditions and applications in image encryption

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CHAOS SOLITONS & FRACTALS 2024年 180卷

作者： Guo, Pengteng Shi, Qiqing Jian, Zeng Zhang, Jing Ding, Qun Yan, Wenhao Heilongjiang Univ Elect Engn Coll Harbin 150080 Peoples R China

Due to the maturation of research on chaos and secure communication, the control technology of nonlinear systems, specifically chaos synchronization, has captured the attention of numerous researchers. Focusing on the issues of inflexibility in the design of chaotic synchronization controllers, the need for prior synchronization of the target system structure, and noise's disruptive impact on synchronization, this paper presents solutions that enhance the practical application of chaos. Firstly, the RBF neural controller is adjusted in this paper to bolster the control precision of the chaotic system and enhance its resilience to external disturbances. Secondly, this article presents an enhanced PSO optimization algorithm for the improved RBF neural controller to improve the optimization efficiency of the controller parameters. Finally, the simulation results of the Lorenz system validate the feasibility of the proposed synchronization control scheme. Additionally, the use of chaotic synchronization in image encryption demonstrates that synchronization accuracy can fulfill the requirements of image encryption application scenarios.

关键词： Neural controller RBF optimization algorithm External disturbance Continuous chaotic system Chaotic synchronization

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algorithms for Smooth, Safe and Quick Routing on Sensor-Equipped Grid Networks

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SENSORS 2021年第24期21卷 8188-8188页

作者： Andreatta, Giovanni De Francesco, Carla De Giovanni, Luigi Univ Padua Dipartimento Matemat Tullio Levi Civita I-35122 Padua Italy

Automation plays an important role in modern transportation and handling systems, e.g., to control the routes of aircraft and ground service equipment in airport aprons, automated guided vehicles in port terminals or in public transportation, handling robots in automated factories, drones in warehouse picking operations, etc. Information technology provides hardware and software (e.g., collision detection sensors, routing and collision avoidance logic) that contribute to safe and efficient operations, with relevant social benefits in terms of improved system performance and reduced accident rates. In this context, we address the design of efficient collision-free routes in a minimum-size routing network. We consider a grid and a set of vehicles, each moving from the bottom of the origin column to the top of the destination column. Smooth nonstop paths are required, without collisions nor deviations from shortest paths, and we investigate the minimum number of horizontal lanes allowing for such routing. The problem is known as fleet quickest routing problem on grids. We propose a mathematical formulation solved, for small instances, through standard solvers. For larger instances, we devise heuristics that, based on known combinatorial properties, define priorities, and design collision-free routes. Experiments on random instances show that our algorithms are able to quickly provide good quality solutions.

关键词： automated transportation network collision-free routing grid network optimization algorithm integer linear programming heuristics

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Parameters Identification of Proton Exchange Membrane Fuel Cell Model Based on the Lightning Search algorithm

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ENERGIES 2022年第21期15卷 7893页

作者： Mohanty, Banaja Elavarasan, Rajvikram Madurai Hasanien, Hany M. Devaraj, Elangovan Turky, Rania A. Pugazhendhi, Rishi Veer Surendra Sai Univ Technol VSSUT Dept Elect Engn Burla 768018 India Univ Queensland Sch Informat Technol & Elect Engn St Lucia Qld 4072 Australia Ain Shams Univ Fac Engn Elect Power & Machines Dept Cairo 11517 Egypt Vellore Inst Technol VIT TIFAC CORE Vellore 632014 Tamil Nadu India Vellore Inst Technol VIT Sch Elect Engn Vellore 632014 Tamil Nadu India Future Univ Egypt Fac Engn & Technol Elect Engn Dept Cairo 11835 Egypt Nestl Private Ltd Res & Dev Div Power & Energy Chennai 600091 Tamil Nadu India

The fuel cell is vital in electrical distribution networks as a distributed generation in today's world. A precise model of a fuel cell is extensively required as it rigorously affects the simulation studies' transient and dynamic analyses of the fuel cell. This appears in several microgrids and smart grid systems. This paper introduces a novel attempt to optimally determine all unknown factors of the polymer exchange membrane (PEM) fuel cell model using a meta-heuristic algorithm termed the Lightning search algorithm (LSA). In this model, the current-voltage relationship is heavily nonlinear, including several unknown factors because of the shortage of fuel cell data from the manufacturer's side. This issue can be treated as an optimization problem, and LSA is applied to detect its ability to solve this problem accurately. The objective function is the sum of the squared error between the estimated output voltage and the measured output voltage of the fuel cell. The constraints of the optimization problem involve the factors range (lower and upper limit). The LSA is utilized in minimizing the objective function. The effectiveness of the LSA-PEM fuel cell model is extensively verified using the simulation results performed under different operating conditions. The simulation results of the proposed model are compared with the measured results of three commercial fuel cells, such as Ballard Mark V 5 kW, BCS 500 W and Nedstack PS6 6 kW, to obtain a realistic study. The results of the proposed algorithm are also compared with different optimized models to validate the model and, further, to determine where LSA stands in terms of precision. In this regard, the proposed model can yield a lower SSE by more than 5% in some cases and high performance of the LSA-PEMFC model. With the results obtained, it can be concluded that LSA prevails as a potential optimization algorithm to develop a precise PEM fuel cell model.

关键词： parameters identification lightning search algorithm (LSA) PEM fuel cell optimization algorithm fuel cell model

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Modeling and optimizing in vitro seed germination of industrial hemp (Cannabis sativa L.)

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INDUSTRIAL CROPS AND PRODUCTS 2021年 170卷 113753-113753页

作者： Hesami, Mohsen Pepe, Marco Monthony, Adrian Scott Baiton, Austin Jones, Andrew Maxwell Phineas Univ Guelph Dept Plant Agr Guelph ON N1G 2W1 Canada

In vitro seed germination of cannabis as the first physiological stage in the plant life cycle is not only important for studying factors affecting cultivation conditions but also crucial for obtaining juvenile tissue as a potential explant for different in vitro procedures. On the other hand, in vitro seed germination is a multi-variable biological process that can be influenced by genetic (genotype) and physical factors (medium composition and environ-mental conditions). Therefore, a powerful mathematical methodology such as artificial neural networks (ANNs) is well suited to analyze the data and optimize the conditions this complex system. The current study was aimed to evaluate the effect of different types and concentrations of carbohydrate sources (sucrose and glucose) as well as different strengths of DKW (Driver and Kuniyaki Walnut) and mMS (Murashige and Skoog Medium, Van der Salm modification) media on seed germination indices as well as morphological features of in vitro-grown cannabis seedlings by using three ANNs including multilayer perceptron (MLP), radial basis function (RBF), and generalized regression neural network (GRNN). The GRNN model displayed higher predictive accuracy (r(2)>0.70) in both training and testing sets for all germination indices and morphological traits in comparison to RBF or MLP. Moreover, non-dominated sorting genetic algorithm-II (NSGA-II) was subjected to the GRNN to find the optimal type and level of media and carbohydrate source for obtaining the best seed germination indices (germination rate and mean germination time). According to the optimization process, 0.43 strength mMS medium supplemented with 2.3 % sucrose would result in the best outcomes. This result showed that a moderate level of salts existing in culture media (0.43 strength of mMS medium) supplemented with a moderate level of sucrose (2.3 %) can improve in vitro seed germination of hemp. The results of a validation experiment revealed that there was a neglig

关键词： Artificial intelligence Carbohydrate sources Culture medium Machine learning algorithm optimization algorithm Plant tissue culture

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