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Developing a management and operation model for water and wastewater components using the equilibrium optimization algorithm

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WATER SUPPLY 2024年第3期24卷 643-664页

作者： Kilic, Selami Ates, Abdullah Firat, Mahmut Yilmaz, Salih Malatya Water & Sewerage Adm Malatya Turkiye Inonu Univ Comp Engn Dept Malatya Turkiye Inonu Univ Civil Engn Dept Malatya Turkiye Cankiri Karatekin Univ Civil Engn Dept Cankiri Turkiye

A novel optimization model was developed using the equilibrium optimization algorithm to define the most appropriate management process according to the current state of urban water components in utilities. The basis of the optimization model is the current status analysis and management system, which consists of 11 main headings and 231 components. This model is applied for three utilities, and the results are presented in comparison with real-time data. Currently, the number of components with 0 or 1 score is 28, 19 and 69, respectively. The current average scores of the components in the utilities were obtained as 2.84, 3.43 and 2.48, respectively. Then, the improvement process of these components is optimized by the equilibrium optimization algorithm. The most appropriate targets were defined as 3.90, 4.15 and 3.71, respectively, with the optimization algorithm by considering the current scores in the utilities. The target scores for water supply, wastewater collection and treatment components are determined as 3.81, 4.05 and 3.84 for utility I;4.03, 4.18 and 4.22 for utility II;and 3.51, 3.56 and 4.05 for utility III. The proposed model will be a reference for defining the most appropriate target and determining the management process.

关键词： equilibrium optimization algorithm optimization wastewater management water distribution system water management

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Rule-Based Arabic Sentiment Analysis using Binary equilibrium optimization algorithm

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2023年第2期48卷 2359-2374页

作者： Rahab, Hichem Haouassi, Hichem Laouid, Abdelkader Abbes Laghrour Univ ICOSI Lab BP 1252 El Houria 40004 Khenchela Algeria El Oued Univ LIAP Lab POB 789 El Oued 39000 Algeria

With the development of websites and social networks, Internet users generate a massive amount of comments and information on the Web. Sentiment analysis, also called opinion mining, offers an opportunity to mine the people's sentiments and emotions from the textual comments. In the last decade, sentiment analysis has been applied in research areas such as recommendation and support systems and has become an area of interest for many researchers. Therefore, many studies have been carried out on English, while other languages, such as Arabic, received less attention. Increasingly, sentiment analysis researchers use machine learning due to its excellent performance. However, the generated models are black boxes and non-interpretable by the users. The rule-based classification is a promising approach for generating interpretable models. This work proposes a classification rule-based Arabic sentiment analysis approach together with a new binary equilibrium optimization metaheuristic algorithm as an optimization method for classification rule generation from Arabic documents. The proposed approach has been experimented on the Opinion Corpus for Arabic (OCA) and generates a classification model of thirteen rules. The comparison results with state-of-the-art methods show that the proposed approach outperforms all other white-box models regarding classification accuracy.

关键词： Sentiment analysis Rule-based classification Arabic Natural language processing Associative classification equilibrium optimization algorithm

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Generic multidimensional economic environmental operation of power systems using equilibrium optimization algorithm

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SCIENTIFIC REPORTS 2025年第1期15卷 1-51页

作者： Mouwafi, Mohamed T. El-Ela, Adel A. Abou El-Hamoly, Amany A. El-Sehiemy, Ragab A. Menoufia Univ Fac Engn Dept Elect Engn Shibin Al Kawm 32511 Egypt Kafrelsheikh Univ Fac Engn Dept Elect Engn Kafrelsheikh 33511 Egypt Szecheny Istvan Univ Sustainabil Competence Ctr Egyet Sq 1 H-9026 Gyor Hungary

The economic emission load dispatch (EELD) problem is one of the main challenges to power system operators due to the complexity of the interconnected power systems and the non-linear characteristics of the objective functions (OFs). Therefore, the EELD problem has attracted significant attention in the electric power system because it has important objectives. Thus, this paper proposes the equilibrium optimization algorithm (EOA) to solve the EELD problem in electrical power systems by minimizing the total fuel cost and emissions, considering system and operational constraints. The OFs are optimized with and without considering valve point effects (VPE) and transmission system loss. The multi-OF, which aims to optimize these objectives simultaneously, is considered. In the proposed EOA, agents are particles and concentrations that express the solution and position, respectively. The proposed EOA is evaluated and tested on different-sized standard test systems having 10, 20, 40, and 80 generation units through several case studies. The numerical results obtained by the proposed EOA are compared with other optimization techniques such as grey wolf optimization, particle swarm optimization (PSO), differential evolution algorithm, and other optimization techniques in the literature. To show the reliability of the proposed algorithm for solving the considered OFs on a large-scale power system with and without considering different practical constraints such as VPE, ramp-rate limits (RRL), and prohibited operating zones (POZs) of generating units, the proposed EOA is evaluated and tested on the 140-unit test system. Also, the proposed multi-objective EOA (MOEOA) successfully acquires the Pareto optimal front to find the best compromise solution between the considered OFs. Also, the statistical analysis and the Wilcoxon signed rank test between the EOA and other optimization techniques for solving the EELD problem are performed. From numerical results, the total fuel cost

关键词： Economic emission load dispatch Emission equilibrium optimization algorithm Generation cost function Valve-points effects

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Optimizing multi-chiller dispatch in HVAC system using equilibrium optimization algorithm

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ENERGY REPORTS 2021年 7卷 5997-6013页

作者： Sun, Fukang Yu, Junqi Zhao, Anjun Zhou, Meng Xian Univ Architecture & Technol Xian Peoples R China Anhui Jianzhu Univ Anhui Prov Key Lab Intelligent Bldg & Bldg Energy Hefei Peoples R China Minist Educ Engn Res Ctr Bldg Energy Efficiency Control & Eva Hefei Peoples R China

The HVAC (heating, ventilation and air-conditioning) system accounts for almost half of the total electricity consumption in buildings, and the chillers in HVAC system are the major energy consumers. Hence, it is significant to reasonably control the chillers for satisfying the thermal comfort demand of occupancy according to indoor environment change, and avoiding excessive cooling output and saving energy consumption. equilibrium optimization (EO) algorithm is a novel physics-based meta-heuristics algorithm which originates from the dynamic mass balance equation. This paper attempts to optimize chiller load dispatch of HVAC system for energy conversation with EO algorithm. To validate the effectiveness of EO algorithm in solving optimal chiller loading (OCL) problem, three well-known cases are utilized to implement simulation experiments. Moreover, the effects of different particle number and parameter setting of EO algorithm on the optimization results are discussed. The experiment results demonstrate that EO algorithm can find out the optimal solution in solving OCL problem with less particles (the minimum equals 10). The optimal solutions are obtained in less than 200 iterations in case 1, 150 iterations in case 2, 50 iterations in case 3, respectively. Comparing with traditional optimization algorithms, the optimum power consumption using EO algorithm can obtain the best solutions, and simultaneously is better than AVL (Average Loading) and SA (Simulated Annealing) algorithm in case 1, AVL and GA (Genetic algorithm) algorithm in case 2, AVL and GA algorithm in case 3, respectively. Moreover, Friedman test and Wilcoxon signed ranks test are also performed to prove efficiency of EO algorithm in solving OCL problem. In conclusion, EO algorithm is suitable for solving OCL problem and has the good performance. (C) 2021 The Author(s). Published by Elsevier Ltd.

关键词： Heating, ventilation and air-conditioning system Optimal chiller loading equilibrium optimization algorithm Energy conversation

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Optimum design of linear and circular antenna arrays using equilibrium optimization algorithm

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INTERNATIONAL JOURNAL OF MICROWAVE AND WIRELESS TECHNOLOGIES 2021年第9期13卷 986-997页

作者： Durmus, Ali Kurban, Rifat Kayseri Univ Dept Elect & Energy Vocat Coll Kayseri Turkey Kayseri Univ Dept Comp Technol Vocat Coll Kayseri Turkey

In this paper, equilibrium optimization algorithm (EOA), which is a novel optimization algorithm, is applied to synthesize symmetrical linear antenna array and non-uniform circular antenna array (CAA). The main purpose of antenna array synthesis is to achieve a radiation pattern with low maximum side lobe level (MSL) and narrow half-power beam width (HPBW) in far-field. The low MSL here is an important parameter to reduce interference from other communication systems operating in the same frequency band. A narrow HPBW is needed to achieve high directionality in antenna radiation patterns. Entering the literature as a novel optimization technique, EOA optimally determined the amplitude and position values of the array elements to obtain a radiation pattern with a low MSL and narrow HPBW. The EOA is inspired by models of the control volume mass balance used to predict equilibrium as well as dynamic states. To demonstrate the flexibility and performance of the proposed algorithm, 10-element, 16-element and 24-element linear arrays and eight-element, 10-element and 12-element CAAs are synthesized. The MSL and HPBW values of radiation pattern obtained with the EOA are very successful compared to the results of other optimization methods in the literature.

关键词： Antenna array synthesis circular antenna array equilibrium optimization algorithm linear antenna array maximum side lobe level

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The equilibrium optimization algorithm and the response surface based metamodel for optimal structural design of vehicle components

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MATERIALS TESTING 2020年第5期62卷 492-496页

作者： Ozkaya, Huseyin Yildiz, Mustafa Yildiz, Ali Riza Bureerat, Sujin Yildiz, Betul Sultan Sait, Sadiq M. Isringhausen Aunde Tekn Bursa Turkey Bursa Uludag Univ Dept Automot Engn Bursa Turkey KFUPM Ctr Commun & IT Res Dhahran Saudi Arabia Khon Kaen Univ Dept Mech Engn Khon Kaen Thailand

Due to harsh competitive conditions and the transition to new vehicles such as hybrid and full-electrical, the interest in the design of light and low-cost vehicles is increasing. In this paper, a recent metaheuristic procedure which is an equilibrium optimization algorithm (EOA) is used to solve a structural design optimization problem for a vehicle seat bracket to prove how the EOA can be used in solving industrial design problems. This paper is the first application of the EAO to real-world problems in the literature. The results strongly prove the capability of the EOA for designing optimum components in the automotive industry.

关键词： equilibrium optimization algorithm seat bracket structural optimization vehicle design

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Robust Optimal Dispatching of Wind Fire Energy Storage System Based on equilibrium optimization algorithm

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FRONTIERS IN ENERGY RESEARCH 2021年 9卷

作者： Chen, Xiaojiao Huang, Liansheng Zhang, Xiuqing He, Shiying Sheng, Zhicai Wang, Zhenshang Chen, Tao Dou, Sheng Chinese Acad Sci Inst Plasma Phys Hefei Peoples R China Univ Sci & Technol China Hefei Peoples R China

The uncertainty of wind resources is one of the main reasons for wind abandonment. Considering the uncertainty of wind power prediction, a robust optimal dispatching model is proposed for the wind fire energy storage system with advanced adiabatic compressed air energy storage (AA-CAES) technology. Herein, the operation constraints of the power plant and constraints of the reserved capacity are defined according to the operation characteristics of AA-CAES. Based on the limited scenario method, a solution framework is proposed to achieve the optimal robustness and economical operation of the system, which provides a new way for the application of the intelligent algorithm in the robust optimal dispatching. Specifically, a novel equilibrium optimization algorithm is employed to solve the optimal dispatching problem, which has good global search performance. The proposed solution is validated through simulations based on the IEEE-39 node system. The simulation results verify the effectiveness of the proposed dispatching model and the intelligent solver.

关键词： robust optimal dispatching wind fire energy storage AA-CAES solution framework equilibrium optimization algorithm

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Simulation Research on the Binary equilibrium optimization algorithm 2020

Simulation Research on the Binary Equilibrium Optimization A...

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12th International Conference on Machine Learning and Computing (ICMLC)

作者： Zhao, Juan Gao, Zheng-Ming Jingchu Univ Technol Sch Elect & Informat Engn Jingmen Peoples R China Jingchu Univ Technol Sch Comp Engn Jingmen Peoples R China

ISBN: (纸本)9781450376426

In this paper, we describe the binary version of the newly raised equilibrium optimization algorithm (EOA) we called here. The binary equilibrium optimization (BEO) algorithm is transferred by ways of a series of transfer functions from the continuous domain. Experiments and logic analysis show that the Sigmoid function would not be expected to perform better due to the slow slope of changes in value. Henceforth V-shape functions are raised. Simulation experiments are carried out and verifications are made with benchmark functions to find the best V-shaped transfer function. Experimental results show that the erfFcn named in this paper as follows perform the best and it could represent the V-shaped transfer functions for future work.

关键词： Simulation experiments equilibrium optimization algorithm benchmark functions transfer functions

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Compact Pyramidal dense mixed attention network for Diabetic retinopathy severity prediction under deep learning

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BIOMEDICAL SIGNAL PROCESSING AND CONTROL 2025年 100卷

作者： Gargi, M. Eluri, Rama Krishna Samantray, Om Prakash Hajarathaiah, Koduru Velagapudi Ramakrishna Siddhartha Engn Coll Deemed Dept Informat Technol Vijayawada 520007 Andhra Prades India Narasaraopeta Engn Coll Comp Sci & Engn Narasaraopeta 522601 Andhra Prades India Raghu Engn Coll Comp Sci & Engn Visakhapatnam 531162 Andhra Prades India VIT AP Univ Sch Comp Sci & Engn Amaravati 522237 Andhra Prades India

Diabetic Retinopathy is the leading cause of blindness in people with diabetes. Artificial intelligence and camera technology advancements have enabled the ability to autonomously diagnose the severity of DR. Nevertheless, the existing approaches target only to enhance the classification task as presence and absence. However, the severity classification remains a difficult issue that must be achieved in order to overcome the limitations of present studies. In this paper, a unique DR severity prediction method based on Deep Learning algorithms is proposed. For ophthalmologists, digital fundus images are the most routinely used imaging for screening and determining disease severity. The fundus images are first collected from the Diabetic Retinopathy Dataset and Asia Pacific Tele-Ophthalmology Society (APTOS-2019) datasets and then pre-processed using the Contrastenhanced Non-local means Gaussian filter to remove noise, improve contrast, and sharpen the image. To reduce time complexity and improve the model's ability, the features are extracted using the Excess level attention axial spectral transformer. To reduce convergence and dimensionality concerns, an ideal collection of features is chosen from the retrieved features using the Dual-phase sine equilibrium optimization algorithm. The severity of the DR can be efficiently characterized across multiple classes utilizing the Compact Pyramidal dense mixed attention network model. The CPDenA model is evaluated using numerous DL performance measures such as accuracy, recall, precision, etc. In the APTOS-2019 and DDR datasets, the CPDenA model achieved high accuracy of 97.95% and 98.59%, respectively. When compared to other previous research, the CPDenA model outperformed in predicting DR severity.

关键词： Pyramidal dense mixed attention network Non-local means Gaussian filter equilibrium optimization algorithm Axial spectral transformer Fundus images

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Enhancing PV distributed generator planning in medium-voltage DC distribution networks: A multi-design techno-economic analysis with load demand response

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IET GENERATION TRANSMISSION & DISTRIBUTION 2024年第1期18卷 173-189页

作者： Zellagui, Mohamed Belbachir, Nasreddine Lasmari, Adel Molu, Reagan Jean Jacques Kamel, Salah Univ Batna 2 Fac Technol Dept Elect Engn Batna Algeria Univ Mostaganem Fac Sci & Technol Dept Elect Engn Mostaganem Algeria Univ Constantine 1 Fac Technol Dept Electrotech Constantine Algeria Univ Douala Technol & Appl Sci Lab UIT Douala Douala Cameroon Aswan Univ Fac Engn Dept Elect Engn Aswan Egypt Univ Douala Technol & Appl Sci Lab UIT Douala POB 8689 Douala Cameroon

Distributed generators have grown in significance for the technical and financial operation of electric power systems in recent years. The integration of these generators into the electrical distribution network (EDN) has experienced rapid growth, primarily driven by advancements in renewable energy sources (RESs), particularly photovoltaic distributed generators (PVDGs). With the increasing implementation of solar energy as a RES, designing the optimal integration of PVDGs into medium voltage direct current (MVDC) networks is crucial to comprehensively analyzing technical and economic factors. To address this issue, a new multiple objective function (MOF) is proposed, which combines various techno-economic parameters such as total active power loss (APL), voltage deviation (VD), and the investment cost of PVDGs (ICPVDG) installed in the test system. The objective is to minimize the MOF simultaneously to achieve the optimal incorporation of PVDGs. This study aims to solve the allocation problems related to the location and size of PVDG units in the modified MVDC test systems IEEE 27 and 33-bus. Simulation results demonstrate the superior accuracy and effectiveness of the equilibrium optimization algorithm (EOA) in achieving the minimum MOF. The utilization of multiple PVDG units reduces overall active power losses and improves voltage profiles across all buses. Distributed generators are crucial for electric power systems, especially photovoltaic distributed generators (PVDGs). To optimize PVDG integration into medium voltage direct current (MVDC) networks, a new multiple objective function (MOF) is proposed. This function combines techno-economic parameters like total active power loss, voltage deviation, and investment cost. The study aims to solve allocation problems in modified MVDC test systems IEEE 27 and 33-bus. Simulation results show superior accuracy and effectiveness of the equilibrium optimization ***

关键词： Photovoltaic distributed generator optimal integration techno-economic evaluation equilibrium optimization algorithm direct current distribution networks

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