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dolphin echolocation algorithm for small-signal stability analysis of DFIG-based wind power system

INTERNATIONAL JOURNAL OF ENGINEERING SYSTEMS MODELLING AND SIMULATION 2021年第4期12卷 301-328页

作者： Kashiv, Ashutosh Verma, H. K. SGSITS Dept Elect Engn Indore 452010 Madhya Pradesh India

In this paper stability examination of a doubly-fed induction generator (DFIG) wind turbine system has been done. DFIG wind turbine system is modelled using the state-space method. The main aim of the paper is to examine the behaviour of the DFIG at the various speeds of the rotor. This paper mentions the application of the proportional-integral controller optimised by dolphin echolocation optimisation algorithm (DEOA) to get efficient as well as stable operation of the DFIG system. For this purpose, damping ratios and eigenvalues are taken as a result. The simulation results were compared with those obtained using the particle swarm optimisation (PSO) approach for the proposed DFIG model. Simulation data show that the DEOA-PI controller works well to limit the transient in voltage and current response for the DFIG model under consideration.

关键词： wind energy dolphin echolocation algorithm DEOA doubly-fed induction generator DFIG stability analysis proportional-integral PI proportional-integral controller

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Optimal design of semi-rigid connection steel frame with infilled shear walls using dolphin echolocation algorithm

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STRUCTURES 2023年 57卷

作者： Qiu, Yudong Wang, Zhan Pan, Jianrong Hu, Fangxin South China Univ Technol Sch Civil Engn & Transportat Guangzhou Peoples R China South China Univ Technol State Key Lab Subtrop Bldg Sci Guangzhou Peoples R China South China Univ Technol Sch Civil Engn & Transportat Guangzhou 510640 Peoples R China

In this paper, the dolphin echolocation algorithm (DEA) was applied for optimization. Two different twodimensional semi-rigid connection steel frames with infilled shear walls (SFIWs) were optimized to obtain the minimum weight with constraints on the element stresses and storey drift ratio according to the American Institute of Steel Construction (AISC) Load and Resistance Factor Design requirements. With the proposed method, the specific details of the infilled shear walls are not given during the design process, but are characterized by the lateral stiffness. The designer can decide which types of infilled shear walls are used according to the result obtained from the optimization. The infilled shear walls are modeled as braces with equivalent lateral stiffnesses, while the semi-rigid connections are used to obtain the practical behaviors of the SFIWs. The results demonstrate that the proposed method is suitable for optimizing semi-rigid connection steel frames with infilled shear walls.

关键词： Optimal design Semi-rigid connection steel frame Infilled shear wall dolphin echolocation algorithm Lateral stiffness

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Optimal Design of Semirigid Connection Steel Frame with Steel Plate Shear Walls Using dolphin echolocation algorithm

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BUILDINGS 2022年第10期12卷 1735页

作者： Qiu, Yudong Wang, Zhan Pan, Jianrong Hu, Fangxin Sharma, Shubham Deifalla, Ahmed Farouk South China Univ Technol State Key Lab Subtrop Bldg Sci Guangzhou 510640 Peoples R China Chandigarh Univ Univ Ctr Res & Dev Mech Engn Dept Mohali 140413 Punjab India Qingdao Univ Technol Sch Mech & Automot Engn Qingdao 266520 Peoples R China Future Univ Egypt Struct Engn & Construct Management New Cairo 11835 Egypt

Steel frame with steel plate shear walls (SPSWs) is used to resist lateral loads caused by wind and earthquakes in high-rise buildings. In this load-resisting system, the cost and performance are more efficient than in the moment frame system. Behaviors of beam-to-column connections are assumed to be pinned or fixed to simplify the calculation in the past few decades. However, studies have stated that such a simulation fails to reveal the response of beam-to-column connections. In this paper, a newly developed metaheuristic optimization algorithm-the dolphin echolocation algorithm (DE)-based on foraging prey using echolocation in dolphins is applied as the present study optimizer. Two different two-dimensional semirigid connection steel frames with SPSWs are optimized to obtain the minimum cost of semirigid connection steel frame with steel plate shear walls with constraints to element stresses and story drift ratio according to the American Institute of Steel Construction (AISC) Load and Resistance Factor Design (LFRD). SPSW is modeled as a brace with equivalent lateral stiffness, while the P - Delta effects are considered in the steel frame. Semirigid connections are used to reveal the actual responses of beam-to-column connections. The results demonstrate the proposed method's effectiveness for optimizing semirigid connection steel frames with SPSWs and the interaction between semirigid connections and the SPSWs.

关键词： optimal design semirigid connection steel frame steel plate shear wall dolphin echolocation algorithm lateral stiffness

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Solving Manufacturing Cell Design Problems by Using a dolphin echolocation algorithm 1

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16th International Conference on Computational Science and Its Applications (ICCSA)

作者： Soto, Ricardo Crawford, Broderick Carrasco, Cesar Almonacid, Boris Reyes, Victor Araya, Ignacio Misra, Sanjay Olguin, Eduardo Pontificia Univ Catolica Valparaiso Valparaiso Chile Univ Autonoma Chile Santiago Chile Univ Cient Sur Lima Peru Univ Cent Chile Santiago Chile Univ San Sebastian Fac Ingn & Tecnol Bellavista 7 Santiago 8420524 Chile Covenant Univ Ota Nigeria

ISBN: (数字)9783319420929

ISBN: (纸本)9783319420929

The Manufacturing Cell Design is a problem that consist in organize machines in cells to increase productivity, i.e., minimize the movement of parts for a given product between machines. In order to solve this problem we use a dolphin echolocation algorithm, a recent bio-inspired metaheuristic based on a dolphin feature, the echolocation. This feature is used by the dolphin to search all around the search space for a target, then the dolphin exploits the surround area in order to find promising solutions. Our approach has been tested by using a set of 10 benchmark instances with several configurations, reaching to optimal values for all of them.

关键词： dolphin echolocation algorithm Metaheuristics Manufacturing cell design problems

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DEA-RNN: A Hybrid Deep Learning Approach for Cyberbullying Detection in Twitter Social Media Platform

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IEEE ACCESS 2022年 10卷 25857-25871页

作者： Murshed, Belal Abdullah Hezam Abawajy, Jemal Mallappa, Suresha Saif, Mufeed Ahmed Naji Al-Ariki, Hasib Daowd Esmail Mysore Univ Dept Studies Comp Sci Mysore 570006 Karnataka India Amran Univ Coll Engn & IT Dept Comp Sci Amran Yemen Deakin Univ Fac Sci Engn & Built Environm Sch Informat Technol Geelong Vic 3220 Australia VTU Dept Comp Applicat Sri Jayachamarajendra Coll Engn JSSTI Campus Mysore 570006 Karnataka India Taiz Univ Al Saeed Fac EngineeringandInformat Technol Dept Comp Networks & Distributed Syst Taizi Yemen Sanaa Community Coll Dept Comp Networks Engn & Technol Sanaa Yemen

Cyberbullying (CB) has become increasingly prevalent in social media platforms. With the popularity and widespread use of social media by individuals of all ages, it is vital to make social media platforms safer from cyberbullying. This paper presents a hybrid deep learning model, called DEA-RNN, to detect CB on Twitter social media network. The proposed DEA-RNN model combines Elman type Recurrent Neural Networks (RNN) with an optimized dolphin echolocation algorithm (DEA) for fine-tuning the Elman RNN's parameters and reducing training time. We evaluated DEA-RNN thoroughly utilizing a dataset of 10000 tweets and compared its performance to those of state-of-the-art algorithms such as Bi-directional long short term memory (Bi-LSTM), RNN, SVM, Multinomial Naive Bayes (MNB), Random Forests (RF). The experimental results show that DEA-RNN was found to be superior in all the scenarios. It outperformed the considered existing approaches in detecting CB on Twitter platform. DEA-RNN was more efficient in scenario 3, where it has achieved an average of 90.45% accuracy, 89.52% precision, 88.98% recall, 89.25% F1-score, and 90.94% specificity.

关键词： Cyberbullying Blogs Feature extraction Support vector machines Recurrent neural networks Training Numerical models Cyber-bullying tweet classification dolphin echolocation algorithm Elman recurrent neural networks short text topic modeling cyberbullying detection social media

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dolphin echolocation - Based Sizing algorithm for Stand-Alone Photovoltaic System 4

Dolphin Echolocation - Based Sizing Algorithm for Stand-Alon...

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4th IEEE International Conference on Applied System Invention (IEEE ICASI)

作者： Othman, Zulkifli Sulaiman, Shahril Irwan Musirin, Ismail Omar, Ahmad Maliki Shaari, Sulaiman Univ Teknol MARA Fac Elect Engn Shah Alam Selangor Malaysia Univ Teknol MARA Fac Appl Sci Shah Alam Selangor Malaysia

ISBN: (纸本)9781538643426

This paper presents a sizing optimization technique for Stand-Alone Photovoltaic (SAPV) system. Three optimization techniques were developed, namely dolphin echolocation (DE), Fast Evolutionary Programming (FEP) and Classical Evolutionary Programming (CEP). These techniques had been incorporated into the sizing process to maximize the Performance Ratio (PR) of the system by determining the optimal PV modules, charge controllers, inverters, and batteries. The results showed that DE outperformed FEP and CEP in producing the highest PR.

关键词： Stand-Alone Photovoltaic dolphin echolocation algorithm Fast Evolutionary Programming Classical Evolutionary Programming Iterative Sizing algorithm

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Fuzzy Inspired Deep Belief Network for the Traffic Flow Prediction in Intelligent Transportation System Using Flow Strength Indicators

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BIG DATA 2020年第4期8卷 291-307页

作者： George, Shiju Santra, Ajit Kumar Vellore Inst Technol Sch Informat Technol & Engn Vellore Tamil Nadu India Amal Jyothi Coll Engn Kottayam Kerala India

Intelligent transportation system (ITS) is an advance leading edge technology that aims to deliver innovative services to different modes of transport and traffic management. Traffic flow prediction (TFP) is one of the key macroscopic parameters of traffic that supports traffic management in ITS. Growth of the real-time data in transportation from various modern equipments, technology, and other resources has led to generate big data, posing a huge concern to deal with. Recently, deep learning (DL) techniques have demonstrated the capability to extract comprehensive features efficiently, using multiple hidden layers, from such huge raw, unstructured, and nonlinear data. Nonlinearity in traffic data is the major cause of inaccuracy in TFP. In this article, we propose a flow strength indicator-based Chronological dolphin echolocation-Fuzzy, a bioinspired optimization method with fuzzy logic for incremental learning of deep belief network. Technical indicators provide flow strength features as an input to the model. Hidden layers of DL architecture consequently learn more features and propagate it as an input to next layer for supervised learning. The degree of membership to the features is identified by the membership functions, followed by weight optimization using dolphin echolocation algorithm to fit the model for the nonlinear data. Experiments performed on two different data sets, namely Traffic-major roads and performance measurement system-San Francisco (PEMS-SF), show good results for the proposed deep architecture. The analysis of the proposed method using log mean square error and log root mean square deviation acquires a minimum value of 2.4141 and 0.61 for the Traffic-major roads database taken for the time step duration of 1 year and a minimum value of 1.6691 and 0.5208 for PEMS-SF data set for the time step interval of 5 minutes, respectively. These positive results demonstrate key importance of our traffic flow model for the transportation system.

关键词： intelligent transportation system traffic flow prediction deep belief network flow strength indicators dolphin echolocation algorithm chronological concept fuzzy theory

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Efficient energy management of hybrid renewable energy sources-based smart-grid system using a hybrid IDEA-CFA technique

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INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS 2021年第5期31卷

作者： Kommula, Bapayya Naidu Song, Heqing Chen, Liang Xu, Chunxiang Aditya Engn Coll Elect & Elect Engn Surampalem Andhra Pradesh India Zhejiang Gongshang Univ Hangzhou Coll Commerce Hangzhou Peoples R China Zhengzhou Univ Technol Dept Civil Engn Zhengzhou Henan Peoples R China Zhengzhou Univ Technol Zhengzhou Henan Peoples R China

A hybrid technique-based energy management scheme for optimal sizing of solar, wind, battery along the integral of pumped hydro storage (PHS) is presented in this paper. The suggested control scheme is the consolidated implementation of both Improved dolphin echolocation algorithm (IDEA) and Cuttlefish algorithm (CFA). Searching behavior of dolphin echolocation algorithm (DEA) is changed through utilizing productive search capacities such as levy flight, so it is known as IDEA. The prominent intension of this work is the optimal energy management in between the source side as well as load side also the total cost function minimization through the suggested IDEA-CFA control procedure. In the proposed work, the IDEA joined with CFA develops the appraisal approach for setting specific control signals to the system as well as generating control signals to disconnected path in subject to power assortment in between the source side as well as load side. Based on equality as well as inequality constraints, the objective function is classified by system data. The suggested model is implemented at MATLAB/Simulink work site as well as execution will be evaluated along the present strategies. The annualized cost and lifetime of HRES considering the system component with capital cost, operation and maintenance cost, replacement cost and lifetime are analyzed. The system component such as PV, Wind, BESS, water pump, water turbine, and upper reservoir are analyzed. The capital cost, operation and maintenance cost, replacement cost and lifetime of PV are 865 [$/kW], 18 [$/year], 865 [$/kW], and 25 [year].

关键词： cuttlefish algorithm dolphin echolocation algorithm energy management hybrid renewable energy sources optimal sizing

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dolphin echolocation - Based Sizing algorithm for Stand-Alone Photovoltaic System

Dolphin Echolocation - Based Sizing Algorithm for Stand-Alon...

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International Conference on Applied System Innovation

作者： Zulkifli Othman Shahril Irwan Sulaiman Ismail Musirin Ahmad Maliki Omar Sulaiman Shaari Faculty of Electrical Engineering Universiti Teknologi MARA Selangor Malaysia Faculty of Applied Sciences Universiti Teknologi MARA Selangor Malaysia

关键词： Stand-Alone Photovoltaic dolphin echolocation algorithm Fast Evolutionary Programming Classical Evolutionary Programming Iterative Sizing algorithm

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Hybrid optimisation for priority-based scheduling in multi-user STBC-MIMO-OFDM

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IET COMMUNICATIONS 2019年第20期13卷 3391-3400页

作者： Raut, Shital N. Jalnekar, Rajesh M. Vishwakarma Inst Technol Pune 411037 MH India

Resource allocation in wireless communication systems is of great concern in order to guarantee the efficient utilisation of scary resources. In space-time block codes-based multiple-input multiple-output with orthogonal frequency division multiplexing (STBC-MIMO-OFDM) system, scheduling the appropriate user to the available antenna is the major challenge. To overcome the challenge, this study proposes a priority-based scheduling mechanism using the hybrid optimisation, dolphin-Rider Optimisation (DRO), which is a combination of dolphin echolocation algorithm and Rider Optimisation algorithm. The prioritisation follows the power and quality of service constraints of the users in such a way that the energy efficiency is enabled in the system. The performance of the system is analysed using the Rayleigh and Rician channels with the transmission media as, text, audio, and image. Moreover, the comparative analysis of the proposed DRO is enabled using three modulation schemes, Binary Phase Shift Keying (BPSK), Quadrature Phase Shift Keying, and quadrature amplitude modulation. The proposed user scheduling mechanism with the BPSK modulation is found to be effective with a minimal bit error rate and maximal throughput of 3.78x10(-7) and 0.875.

关键词： MIMO communication space-time codes block codes scheduling Rician channels OFDM modulation quadrature phase shift keying phase shift keying quadrature amplitude modulation error statistics resource allocation available antenna priority-based scheduling mechanism hybrid optimisation dolphin-Rider Optimisation DRO dolphin echolocation algorithm Rider Optimisation algorithm quality service constraints energy efficiency Binary Phase Shift Keying Quadrature Phase Shift Keying quadrature amplitude modulation user scheduling mechanism multiuser STBC-MIMO-OFDM resource allocation wireless communication systems efficient utilisation scary resources space-time block codes-based multiple-input appropriate user

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