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25th Signal Processing and Communications Applications Conference (SIU)

作者： Koza, Turker Karaboga, Nurhan Bozok Univ Elekt Program Yozgat Turkey Erciyes Univ Elekt Elekt Muhendisligi Bolumu Kayseri Turkey

ISBN: (纸本)9781509064946

This paper presents a frequency domain signal based design method for quadrature mirror filter (QMF) banks. the proposed filter banks performances were examined and evaluated for the time domain signals In designs, the artificially generated EEG signal and its FFT transform was used. The prototype filter of the QMF bank parameters are designed with artificial bee colony (abc) algorithm. In time and frequency domain designed QMF bank performances are compared and interpreted.

关键词： QMF bank design abc algorithm Fast Fourier transform EEG

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An Adaptive Approach for RFID Based Data Dissemination in VANETs Through abc algorithm Using Android Mobiles 4

An Adaptive Approach for RFID Based Data Dissemination in VA...

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4th IEEE International Conference on Artificial Intelligence with applications in Engineering and Technology (ICAIET)

作者： Lalitha, R. V. S. Suma, Jaya G. Sri Sai Aditya Inst Sci & Technol Dept Comp Sci & Engn Surampalem India JNTUK Univ Coll Engn Dept Informat Technol Vizianagaram India

ISBN: (纸本)9781479979103

Recent applications on Vehicular Ad Hoc Networks(VANET) focus on safety driving and rescue operations involved freeing from danger situations. Geo Locations of the vehicles can be obtained using Geographic Position System(GPS). As well, RFID assisted vehicles can have Location Information(Latitude and Longitude positions of the Vehicles) written through tags. By comparing the location information obtained from GPS and RFID information gathered from tags, the performance of the transmission mechanism is levered. The proposed approach uses RFID tags on the road side at danger locations and at junctions. In this paper, RFID assisted vehicles reads data written in RFID tags using RFID readers in the mobiles automatically for taking vital decisions. This reduces the forwarding of counterfeit messages over VANETs as the messages transmitted using GSM communication is retraced with the data stored in the RFID tags. This could be a better cost effective approach as the RFID tags are less in cost. The derived solution is optimized using abc(Artificial Bee Colony) algorithm as this approach provides attractive methodology in obtaining information from the neighborhoods.

关键词： VANET abc algorithm Broadcasting GCM Services Location Information

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A PAPR Reduction Scheme based on Improved PTS with abc algorithm for OFDM Signal 15

A PAPR Reduction Scheme based on Improved PTS with ABC Algor...

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15th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)

作者： Mata, Tanairat Boonsrimuang, Pisit Boontra, Pitchaya Rajamangala Univ Technol Krungthep RMUTK Fac Engn Bangkok 10120 Thailand KMITL Fac Engn Bangkok 10520 Thailand

ISBN: (纸本)9781538635551

A high PAPR is well known as the serious problem of OFDM system because of a huge degradation of its signal quality, especially in the non-linear channel. From the reason, many PAPR reduction schemes have been proposed for solving this problem. The Partial Transmit Sequence (PTS) scheme is one of the PAPR reduction schemes which can improve the PAPR performance effectively. However, its computational complexity would be increased which is proportional to the increasing number of symbol clusters in the optimum PAPR value for a PAPR reduction process. To solve this problem, this paper proposes the PAPR reduction scheme based on the improved PTS with Artificial Bee Colony (abc) algorithm for OFDM system. The potential capability of the proposed scheme is the PAPR reduction performance with low computational complexity which leads to the improvement of signal quality in the OFDM system. The excellent PAPR reduction performance with the low computational complexity of the proposed scheme has been verified by the computer simulations in this paper.

关键词： high PAPR OFDM PAPR reduction scheme improved PTS abc algorithm

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Fuzzy-Stochastic Advance Payment Inventory Model Having No Shortage and with Uniform Demand Using abc algorithm

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International Journal of Applied and Computational Mathematics 2018年第4期4卷 1-19页

作者： Supakar, P. Mahato, S.K. Department of Mathematics Sidho-Kanho-Birsha University Purulia 723104 India

Advance payment is an important issue in inventory models. We, see that the policy of advance payments is of common practice in the today’s market environment. In this paper, an inventory model with advance payment for a single item has been developed. In this model the lead time is taken to be stochastic and also there is no shortage. The crisp model has been developed with these characteristics first. Then the corresponding fuzzy model is formulated. In the fuzzy model, several inventory parameters involved, are taken as parabolic-flat fuzzy numbers. So, finally, the model becomes a fuzzy-stochastic model due to the reason that the lead time is stochastic. The very effective graded mean integration representation method has been used to convert the fuzzy numbers into the crisp numbers. Then the crispified fuzzy-stochastic model has been solved using abc algorithm. Finally, some numerical examples are presented to illustrate the model and the solution methodology. The effects of change of different inventory parameters have been studied and are presented both in tabular form and graphically. © 2018, Springer (India) Private Ltd., part of Springer Nature.

关键词： abc algorithm Advance payment Fuzzy number Fuzzy-stochastic Inventory model Parabolic-flat fuzzy numbers

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Detection and Modeling of Alcohol Intoxication Dynamic from IR Images Based on Clustering Driven by abc algorithm 11th

Detection and Modeling of Alcohol Intoxication Dynamic from ...

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11th International Conference on Computational Collective Intelligence (ICCCI)

作者： Kubicek, Jan Krestanova, Alice Penhaker, Marek Oczka, David Cerny, Martin Augustynek, Martin VSB Tech Univ Ostrava FEECS K45017 Listopadu 15 Ostrava Czech Republic

ISBN: (纸本)9783030283773;9783030283766

Alcohol detection is a challenging issue due to many aspects, especially to security reasons. Conventional measuring systems usually utilize a direct contact with the human body to obtain on spot alcohol level estimation. Nevertheless, it is well known that there are several side effects including the facial temperature distribution for alcohol detection. Since the facial temperature map is observable from the infrared (IR) records, we have performed a set of experimental measurements allowing for dynamical tracking of time-dependent effect of the alcohol intoxication. In this paper, we have proposed the clustering multiregional segmentation driven by the genetic optimization, particularly the Artificial Bee Colony (abc) algorithm for the facial IR segmentation. The genetic optimization determines an optimal distribution of the initial cluster's centroids, which represent the main part of a proper clustering. Based on the segmentation procedure, we have proposed a dynamical model allowing for prediction of time-dependent alcohol intoxication features.

关键词： Image segmentation IR image Alcohol features abc algorithm Clustering K-means

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Solving the Multiple choice Multidimensional Knapsack problem with abc algorithm

Solving the Multiple choice Multidimensional Knapsack proble...

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IEEE Congress on Evolutionary Computation (CEC) as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Mkaouar, Arij Htiouech, Skander Chabchoub, Habib Natl Engn Sch Sfax Sfax Tunisia Univ Jeddah CS & AI Dept Jeddah Saudi Arabia Al Ain Univ Sci & Technol Abu Dhabi U Arab Emirates

ISBN: (纸本)9781728169293

The Multidimensional Multiple-choice Knapsack Problem (MMKP) is an NP-hard problem. Many heuristics algorithms have been developed to solve this combinatorial optimization problem. In this work, a new method based on Artificial Bee Colony algorithm (abc) and surrogate constraint is proposed to solve the MMKP. Experimental results show that this method is competitive with the state-of-the-art approaches.

关键词： MMKP abc algorithm Surrogate constraint Combinatorial optimization problem

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abc algorithm-based optimization and evaluation of nano carbon black added multi-layer microwave absorbing ultra weight foam concrete

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MATERIALS TODAY COMMUNICATIONS 2022年 32卷

作者： Yildizel, Sadik Alper Toktas, Abdurrahim Karamanoglu Mehmetbey Univ Engn Fac Dept Civil Engn TR-70200 Karaman Turkey Ankara Univ Engn Fac Dept Artificial Intelligence & Data Engn TR-06830 Ankara Turkey

This research presents a study on the nano-carbon black (NCB) added ultra-weight foam concrete by revealing its potential utilization of multi-layer microwave absorbing foam concrete (MMAFC). The fresh and hardened properties of the foam concrete samples were investigated. Four concrete samples were constituted by adding NCB with 0%, 5%, 10% and 15%. They were microwave characterized so as to achieve complex permittivity and permeability values at the range of 8.2-12.4 GHz. An abc algorithm-based optimization was also conducted to design four MMAFC with number of layer (NL)= 1, 2, 3 and 4. The results showed that dry density of foam concrete samples varied between 167 and 218 kg /m(3), the thermal conductivity between 0.067 and 0.092 W / (mK), indicating better performances compared to the conventional foam concretes within the range of ultra-weight classification. The 4-layer MMAFC with 34.74 mm total thickness excessively satisfies the minimum requirement of 90% absorption (-10 dB reflection coefficient). Therefore, the proposed optimal MMAFC can be used in building for microwave absorbing and shielding.

关键词： Foam Foam concrete Absorbance abc algorithm

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Low-Illumination Image Enhancement algorithm Based on Improved Multi-Scale Retinex and abc algorithm Optimization

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FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY 2022年 10卷 865820页

作者： Sun, Ying Zhao, Zichen Jiang, Du Tong, Xiliang Tao, Bo Jiang, Guozhang Kong, Jianyi Yun, Juntong Liu, Ying Liu, Xin Zhao, Guojun Fang, Zifan Wuhan Univ Sci & Technol Key Lab Met Equipment & Control Technol Minist Educ Wuhan Peoples R China Wuhan Univ Sci & Technol Res Ctr Biomimet Robot & Intelligent Measurement Wuhan Peoples R China Wuhan Univ Sci & Technol Hubei Key Lab Mech Transmiss & Mfg Engn Wuhan Peoples R China Wuhan Univ Sci & Technol Precis Mfg Res Inst Wuhan Peoples R China China Three Gorges Univ Hubei Key Lab Hydroelect Machinery Design & Maint Yichang Peoples R China

In order to solve the problems of poor image quality, loss of detail information and excessive brightness enhancement during image enhancement in low light environment, we propose a low-light image enhancement algorithm based on improved multi-scale Retinex and Artificial Bee Colony (abc) algorithm optimization in this paper. First of all, the algorithm makes two copies of the original image, afterwards, the irradiation component of the original image is obtained by used the structure extraction from texture via relative total variation for the first image, and combines it with the multi-scale Retinex algorithm to obtain the reflection component of the original image, which are simultaneously enhanced using histogram equalization, bilateral gamma function correction and bilateral filtering. In the next part, the second image is enhanced by histogram equalization and edge-preserving with Weighted Guided Image Filtering (WGIF). Finally, the weight-optimized image fusion is performed by abc algorithm. The mean values of Information Entropy (IE), Average Gradient (AG) and Standard Deviation (SD) of the enhanced images are respectively 7.7878, 7.5560 and 67.0154, and the improvement compared to original image is respectively 2.4916, 5.8599 and 52.7553. The results of experiment show that the algorithm proposed in this paper improves the light loss problem in the image enhancement process, enhances the image sharpness, highlights the image details, restores the color of the image, and also reduces image noise with good edge preservation which enables a better visual perception of the image.

关键词： multi-scale retinex weighted guided image filtering abc algorithm bilateral gamma function image enhancement

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Convergence analysis of abc algorithm based on difference model

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APPLIED SOFT COMPUTING 2023年 146卷

作者： Jiang, Ye Qian, Hanxiao Chu, Yili Liu, Jian Jiang, Zhaoneng Dong, Feibiao Jia, Lu Hefei Univ Technol Sch Comp Sci & Informat Engn Hefei 230009 Peoples R China Anhui Med Univ Sch Humanist Med Hefei 230032 Peoples R China

In the cross-mutation phase of the Artificial Bee Colony optimization algorithm (abc algorithm), the value of parameter & phi;is very important to the stability of abc algorithm, however, most literatures did not specify the origin of the value range of parameter & phi;. Through the theoretical analysis of the stability of the abc algorithm, appropriate parameters can be selected for the algorithm under different convergence conditions and different application conditions, and then the rapid convergence of the algorithm can be achieved, so the stability analysis of the algorithm is very worth exploring. This paper firstly introduces the abc algorithm, and then differentiates the motion trajectory equations of employed bees in the abc algorithm to obtain a differential model;then uses the discrete system stability theory to analyze the stability of the system, and obtains the relationship between the value range of the parameters in the cross-mutation stage and the stability of the algorithm. Finally, the correctness of the conclusion will be verified by experiments using the test function. The results obtained show that abc algorithm with & phi;& ISIN;(-2, 0) converges faster, and has better global optimization performance than abc algorithm with other values of & phi;, which are investigated in this paper. & COPY;2023 Elsevier B.V. All rights reserved.

关键词： abc algorithm Motion trajectory Difference model Stability

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Improved Chernoff Bound of Gaussian Q-function with abc algorithm and its QAM applications to DB SC and MRC systems over Beaulieu-Xie channels

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PHYSICAL COMMUNICATION 2023年第1期58卷

作者： Bilim, Mehmet Karaboga, Dervis Nuh Naci Yazgan Univ Elect & Elect Engn Dept TR-38090 Kayseri Turkiye Erciyes Univ Comp Engn Dept TR-38039 Kayseri Turkiye

In this study, we propose an improved upper bound for the Gaussian Q function by using artificial bee colony algorithm. Then, we investigate the performance of the dual-branch (DB) selection combining (SC) and maximal ratio combining (MRC) systems over the Beaulieu-Xie fading channels. The probabil-ity density functions of the instantaneous signal to noise ratio for the considered systems are obtained. Employing the proposed upper bound, we derive closed-form expressions of the error probability for the quadrature amplitude modulation (QAM) techniques such as rectangular QAM (RQAM), cross QAM (XQAM), and hexagonal QAM (HQAM). Furthermore, the asymptotic error probability expressions for the DB SC system are also obtained to simplify the analyses. The effects of some key parameters in the systems are shown in the results. Comparisons of the different modulation types and the different upper bound approaches for the Gaussian Q function are presented. Finally, it has been shown that the upper bound approximation presented in this study can be widely used for many communication applications.(c) 2023 Elsevier B.V. All rights reserved.

关键词： Quadrature amplitude modulation Selection combining Maximal ratio combining Dual-branch Beaulieu-Xie fading Gaussian Q function abc algorithm

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