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3rd International Conference on Computing for Sustainable Global Development (INDIACom)

作者： Girotra, Sanchi Sharma, Kapil Delhi Technol Univ Dept Comp Engn Delhi India

ISBN: (纸本)9789380544199

Software effort estimation is an important process in software development as it predicts the no. of resources required to build the project. Lack of its accuracy and precision will impact timely delivery of project, and its budget. There arc numerous methods to estimate software effort. COCOMO II has been employed because of its wide acceptance as an industry standard and its applicability at diverse stages of software Engineering. And Accuracy in COCOMO II software effort estimation is highly dependent on its input parameters such as size of project, coefficients and cost drivers. Thus small changes in these parameters bring huge differences in Effort estimation. In this paper, we used Nature Inspired - Meta Heuristic bat algorithm to fine tune values of 15 cost drivers, which can effectively reduce error (MMRE) in effort estimation. It has been validated using NASA 93 dataset and its results are found better than COCOMO and genetic algorithm.

关键词： bat algorithm COCOMO II Cost Drivers MMRE MRE NASA 93 Dataset Software Effort Estimation

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Community Detection Using Meta-heuristic Approach: bat algorithm Variants 9

Community Detection Using Meta-heuristic Approach: Bat Algor...

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9th International Conference on Contemporary Computing (IC3)

作者： Sharma, Jigyasha Annappa, B. Natl Inst Technol Karnataka Dept Comp Sci & Engn Surathkal 575025 India

ISBN: (纸本)9781509032518

In the present world, it is hard to overlook - the omnipresence of 'network'. Be it the study of internet structure, mobile network, protein interactions or social networks, they all religiously emphasizes on network and graph studies. Social network analysis is an emerging field including community detection as its key task. A community in a network, depicts group of nodes in which density of links is high. To find the community structure modularity metric of social network has been used in different optimization approaches like greedy optimization, simulated annealing, extremal optimization, particle swarm optimization and genetic approach. In this paper we have not only introduced modularity metrics but also hamiltonian function (potts model) amalgamated with meta-heuristic optimization approaches of bat algorithm and Novel bat algorithm. By utilizing objective functions (modularity and hamiltonian) with modified discrete version of bat and Novel bat algorithm we have devised four new variants for community detection. The results obtained across four variants are compared with traditional approaches like Girvan and Newman, fast greedy modularity optimization, Reichardt and Bornholdt, Ronhovde and Nussinov, and spectral clustering. After analyzing the results, we have dwelled upon a promising outcome supporting the modified variants.

关键词： bat algorithm Novel bat algorithm Modified bat algorithm community detection modularity hamiltonian function social network

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Solving Optimal Load Dispatch Problem Using Enhanced bat Optimization algorithm

Solving Optimal Load Dispatch Problem Using Enhanced BAT Opt...

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Conference on Innovations in Power and Advanced Computing Technologies (i-PACT)

作者： Pradhan, Gunanidhi Dewangan, P. D. Natl Inst Technol Dept Elect Engn Raipur Madhya Pradesh India

ISBN: (纸本)9781509056828

The latest technique on bat algorithm (BA) for simplifying problem on optimization is a recently developed evolutionary algorithm (EA). This paper represents an Enhanced bat algorithm (EBA) for solving problem on economic load dispatch. Its aim is to reduce the total cost of the generating stations (thermal units) having piecewise quadratic cost behaviour subjected to generation Constraints. The results showed that the given method has better problem solving property and give precise result than other algorithms mentioned in newly literature.

关键词： Economic load dispatch Metaheuristic bat algorithm Valve Point Effect Prohibited Zone EBA algorithm

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Solving Manufacturing Cell Design Problems by Using a bat algorithm Approach

Solving Manufacturing Cell Design Problems by Using a Bat Al...

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7th International Conference on Swarm Intelligence (ICSI)

作者： Soto, Ricardo Crawford, Broderick Alarcon, Andres Zec, Carolina Vega, Emanuel Reyes, Victor Araya, Ignacio 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

ISBN: (纸本)9783319410005;9783319409993

Manufacturing Cell Design is a problem that consist in distributing machines in cells, in such a way productivity is improved. The idea is that a product, build up by using different parts, has the least amount of travel on its manufacturing process. To solve the MCDP we use the bat algorithm, a metaheuristic inspired by a feature of the microbats, the echolocation. This feature allows an automatic exploration and exploitation balance, by controlling the rate of volume and emission pulses during the search. Our approach has been tested by using a well-known set of benchmark instances, reaching optimal values for most of them.

关键词： Bio-inspired systems bat algorithm Metaheuristic Manufacturing Cell Design Problems

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A hybrid metaheuristic based on the firefly and bat algorithms to solve the alternative subgraphs assembly line balancing problem

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PRODUCTION ENGINEERING-RESEARCH AND DEVELOPMENT 2024年第3-4期18卷 533-556页

作者： Palamut, Ummuhan Akpinar, Sener Dokuz Eylul Univ Dept Ind Engn TR-35397 Izmir Turkiye

Assembly line balancing problem is the process of assigning a set of tasks to a group of stations, considering the precedence relations between tasks. Precedence relations are commonly definite;however, tasks may have alternative precedence relations due to different mounting alternatives. In the presence of alternative precedence relations, the classical balancing problem becomes more complicated given that two interdependent problems, namely selection and balancing, must be solved hierarchically. This type of balancing problem is named as the Alternative Subgraph Assembly Line Balancing Problem (ASALBP). This current paper concerns itself to develop an efficient solution procedure for the ASALBP by hybridizing the firefly and bat algorithms. The proposed hybrid algorithm is evaluated on a set of benchmark problems taken from the related literature and numerically compared against the standard firefly and bat algorithms, and some formerly developed heuristic methods. Computational results reveal the satisfactory performance of the proposed algorithm in solving ASALBP instances.

关键词： Alternative subgraph assembly line balancing problem Hybrid metaheuristic Firefly algorithm bat algorithm

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Hybrid bat and Salp Swarm algorithm for Feature Selection and Classification of Crisis-Related Tweets in Social Networks

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IEEE ACCESS 2024年 12卷 103908-103920页

作者： Farooqui, Nafees Akhter Hasan, Mohammad Kamrul Noori, Mohammed Ahsan Raza Abd Rahman, Abdul Hadi Islam, Shayla Haleem, Mohammad Ahmad, Sheikh Fahad Khan, Asif Ahmed, Fatima Rayan Awad Babiker, Nissrein Babiker Mohammed Ahmed, Thowiba E. Khan, Atta Ur Rehman Koneru Lakshmaiah Educ Fdn Dept CSE Vaddeswaram Andhra Pradesh India Univ Kebangsaan Malaysia Fac Informat Sci & Technol Bangi 43600 Malaysia DIT Univ Sch Comp Dehra Dun India UCSI Univ Inst Comp Sci & Digital Innovat Kuala Lumpur Malaysia Era Univ Dept Comp Sci Lucknow India GITAM Deemed be Univ Dept Comp Sci & Engn Hyderabad India Integral Univ Dept Comp Sci Lucknow India Prince Sattam Bin Abdulaziz Univ Coll Comp Engn & Sci Comp Sci Dept Al Kharj 16273 Saudi Arabia Imam Abdulrahman Bin Faisal Univ Coll Sci & Humanities Jubail Comp Sci Dept Dammam 35811 Saudi Arabia Univ Bisha Coll Comp & Informat Technol Bisha Informat Syst Dept Bisha 61922 Saudi Arabia Ajman Univ Coll Engn & IT Ajman U Arab Emirates

Twitter is a useful tool for effectively tracking and managing crisis-related incidents. However, due to many irrelevant features in textual data, the problem of high dimensionality arises, which eventually increases the computational cost and decreases classification performance. Thus, to handle such a problem, this work presents a Spark-based hybrid binary bat (BBA) and binary Salp swarm algorithm (BSSA) named SBBASSA for feature selection and classification of crisis-related tweets. In the proposed technique, the hybridization of standard BBA and BSSA algorithms is performed to enhance their exploration capabilities, then the combined algorithm is implemented in parallel using Apache Spark framework to reduce the overall execution time during the feature selection process. A support vector machine (SVM) classifier is applied during the wrapper-based feature subset selection and classification. The performance of the proposed SBBASSA was analyzed on six benchmark crisis tweet datasets, namely Hurricane Sandy, Boston Bombings, Oklahoma Tornado, West Texas Explosion, Alberta Floods, and Queensland Floods, and then compared with standard BSSA, BBA, and binary particle swarm optimization (BPSO). Results showed that SBBASSA performed competently in the feature selection and classification, outperformed other algorithms in crisis tweet classification, and achieved the highest accuracy with the lowest feature set in a reduced execution time.

关键词： Feature extraction Disasters Classification algorithms Social networking (online) Support vector machines Vectors Deep learning Apache spark bat algorithm crisis tweet classification feature selection salp swarm algorithm

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Efficient bat-inspired block matching algorithm with novel motion energy directional histograms for dynamic texture fast recognition

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MULTIMEDIA TOOLS AND APPLICATIONS 2024年第7期83卷 21633-21653页

作者： Bida, Ikram Aouat, Saliha Univ Sci & Technol Houari Boumediene USTHB Dept Comp Sci Algiers 16111 Algeria

Motion estimation is a crucial step in Dynamic Texture (DT) Motion-based recognition systems, as it directly affects the system's overall accuracy and computational proficiency. Whereas efficient motion estimation methods are pixel-based prioritizing recognition quality over computational complexity, this trade-off may not be acceptable in time-sensitive applications. Therefore, Block Matching algorithms (BMA) stand as potential alternative candidates, however, classic BMA often falls into local optimums ambushes resulting suboptimal solutions, particularly for complex motion videos such DT. In this paper, we propose a novel bat-inspired block matching approach for motion estimation to overcome the issue of falling into local optima. Our approach is inspired from the powerful search capacity of the bat algorithm seeking the best block within a search space;aiming accuracy improvement and a faster convergence. Afterwards, we extract motion features from the matched blocks fields to characterize the different DT videos. Two comprehensive sets of experiments were performed to validate the proposed approaches, Firstly the bat-inspired block motion estimation performance was compared against common algorithms on various standard video sequences. Moreover, the effectiveness of the introduced Dynamic Texture Recognition (DTR) system was demonstrated using well-known DT datasets, where comparative studies with state-of-art methods were presented. The results achieved a balance on computational speed and accuracy on multiple datasets.

关键词： bat algorithm Block matching algorithms Dynamic texture recognition Feature extraction Motion estimation PCA

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Multi-Objective Optimal Economic Emission Power Dispatch using bat algorithm

Multi-Objective Optimal Economic Emission Power Dispatch usi...

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International Conference on Innovations in Power and Advanced Computing Technologies

作者： G Ravi Kumar Allaparthi Rohith G Priyanka G Vamsipriya EEE department

ISBN: (纸本)9781509056835

This paper presents bat algorithm based on Environmental and Economy using multi-objective thermal power Dispatch problem which is articulated as a non-inferior solution to the multi-objective problem. The proposed algorithm minimizes both fuel cost and emission simultaneously. Simulation outcomes presented for the standard IEEE 30-bus system using the bat algorithm with Weighted Sum are compared to other former approaches. The combustion of fossil fuel gives rise to particular material and gaseous pollutants apart from the discharge of heat to water courses as by-products. Several contaminants, such as Sulphur oxides, nitrogen oxides and carbon dioxide shows destructive effects on human life. In the Multi-objective problem formulation, there is minimum emission dispatch for in operating strategy, which can ensure minimum pollution level at minimum operating cost. The proposed procedure proves to be dealing competitive in the field of evolutionary algorithms on multi objective optimization problems in comparison with other algorithms.

关键词： Multiobjective optimization genetic algorithms weighting method Bee colony algorithm Economic dispatch bat algorithm

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Numerical study for single and multiple damage detection and localization in beam-like structures using bat algorithm

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JOURNAL OF VIBROENGINEERING 2016年第1期18卷 202-213页

作者： Khatir, Samir Belaidi, Idir Serra, Roger Wahab, Magd Abdel Khatir, Tawfiq Res Team Mech & Syst & Proc Engn Energet Mech & Engn Lab Boumerdes 35000 Algeria INSA Ctr Val Loire LMR Lab Mecan & Rheol 3 Rue Chocolaterie F-41000 Blois Loir & Cher France Univ Ghent Soete Lab Fac Engn & Architecture Technol Pk Zwijnaarde 903 B-9052 Zwijnaarde Belgium Univ Ctr Salhi Ahmed Inst Sci & Technol Naama 45000 Algeria

This paper presents a new damage detection and localization technique based on the changes in vibration parameters using bat and Particle Swarm Optimization algorithm. The finite element method is used to apply damage at specific element(s) of the considered beams. The damage is represented by a reduction in Young's modulus and the identification of damage is formulated as an optimization problem using objective function based on Modal Scale Factor and changes in natural frequencies. A procedure for detecting and locating damage of beam-like structures based on bat algorithm is used. This approach presents a method that can be used to detect the single and multiple-damage positions and the rate of damage in structural elements with high accuracy after the first iteration. The results obtained using bat algorithm are compared to those obtained using Particle Swarm Optimization algorithm. By taking noise into account in the damage detection and localization problem, it is shown that our approach based on bat algorithm can detect the damage locations with high accuracy.

关键词： damage detection localization beam structure particle swarm optimization vibration analysis bat algorithm

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An improved bat algorithms for optimization design of truss structures

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STRUCTURES 2023年 47卷 2240-2258页

作者： Vu-Huu, T. Pham-Van, Sy Pham, Q-Hoan Cuong-Le, Thanh Vietnam Maritime Univ Fac Civil Engn 484 Lach Tray Str Hai Phong Vietnam Ho Chi Minh City Open Univ Ctr Engn Applicat & Technol Solut Ho Chi Minh City Vietnam

This paper exploits a novel improved metaheuristic to entrance the standard bat algorithm (BA) performance for optimization engineering problems and optimization design of truss structures. As is the case with many met-aheuristic algorithms, BA is straightforward to implement, and such a basic algorithm may address a wide variety of problems with great flexibility. However, when its exploitation stage is changed too quickly by rapidly shifting the loudness and pulse emission rate, it may stagnate after an early stage. It could result in a low probability of success in finding the real prey. Therefore, a new loudness function is proposed to adapt the step size of the random walk efficiently. Also, this study proposes a push-process technique that can generates an intervention in the BA algorithm to expose the true global optimal in a few generations instead of many calculation times. Then, all results are validated to those of well-established research. Finally, the proposed BA is applied to optimize the structural weight of truss structures.

关键词： Metaheuristics Optimisation problems bat algorithm Exploration and exploitation

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