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Fuzzy logic coupled with exhaustive search algorithm for forecasting of petroleum economic parameters

JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2019年 176卷 291-298页

作者： Naderi, Meysam Khamehchi, Ehsan Amirkabir Univ Technol Dept Petr Engn Tehran Iran

In the upstream of oil and gas sector, many development plans and strategic decisions are based on economic calculations. Therefore, it is so important to establish novel models for accurate forecasting of economic variables with minimized error. In this study, two rule-based fuzzy inference systems based on Mamdani-type and TSK models coupled with exhaustive search algorithm are applied to forecast monthly oil price (MOP), daily gas price (DGP), and annually interest rate (AIR). All required data were collected from Central Bank of the Islamic Republic of Iran. In addition, autoregressive integrated moving average (ARIMA) model is used as a reasonable benchmark to identify whether the proposed fuzzy based methods can outperform ARIMA models for forecasting of economic factors. The statistical significance of results is evaluated using a bootstrap algorithm and various error criteria. The results show that Mamdani-type outperforms ARIMA and TSK in MOP, DGP, and AIR forecast. The results indicate that optimized Mamdani-type reduces RMSE by 69.19% MOP prediction, by 84.37% in DGP prediction, and by 93.67% in AIR prediction over benchmark method.

关键词： ARIMA Bootstrap algorithm exhaustive search algorithm Forecasting oil and gas price and interest rate Fuzzy logic Mamdani-type and TSK

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The exhaustive search algorithm in the Transport network optimization on the example of Urban Agglomeration Rijeka 42

The Exhaustive Search Algorithm in the Transport network opt...

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42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)

作者： Vukmirovic, Slavomir Capko, Zvonko Babic, Ana Univ Rijeka Fac Econ Ivana Filipovica 4 Rijeka 51000 Croatia

ISBN: (纸本)9789532330984

The paper presents the use of exhaustive search algorithm and model of Traveling Salesman Problem (TSP) in the transport network optimization, on the example of Urban Agglomeration Rijeka. The aim is optimal routing design between cities and municipalities of Urban Agglomeration Rijeka. In creating of Urban Agglomeration Rijeka has been defined the criteria of sustainability of transport and infrastructure systems covering the most important existing and planned economic zones, infrastructure buildings and traffic hubs (rail, highway, port, airport), located in cities and municipalities in the wider Rijeka area. The transport network of Urban Agglomeration Rijeka should provide optimal supply of cities, municipalities, and their distribution centers in the area of agglomeration. Choosing the relevant information technology and computer software to enable us to create optimal node connections (cities, distribution centres, ports, and terminals), and arrange the optimal transportation routes, is the key factor of transportation network modelling for an effective distribution of goods. Visual and object-oriented methods of modelling and programming allows us to use and visualize the exhaustive search algorithm in the transport network optimization, in the way to identify multiple optimal solutions with a clear interpretation of the results not only of the optimal value but also at approximately equal values and their deviations from the optimal value. Given that Urban Agglomeration Rijeka covers 10 cities and municipalities, exhaustive search algorithm is suitable for designing the transport network. In making the program based on the exhaustive search algorithm have been used Visual Basic for Application in Excel spreadsheet interface. The exhaustive search algorithm, with the calculation of the optimal relation, also allows the calculation of suboptimal relations whose values within an acceptable deviation from the optimal value. The calculation and insight into the

关键词： Transport network optimization Travelling Salesman Problem Urban Agglomeration Rijeka exhaustive search algorithm optimal and suboptimal relationships

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Coordinated control strategy for HVDC frequency controllers in multi-area asynchronous grid

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2025年 167卷

作者： Lei, Jianxiong Yang, Rongzhao Wu, Weixiong Lu, Weicheng Mo, Weike Jinan Univ Energy & Elect Res Ctr Zhuhai 519070 Peoples R China China Southern Power Grid Elect Power Res Inst Guangzhou 510663 Peoples R China

Due to the complexity and fragility of large-scale synchronous grids, utilizing High Voltage Direct Current (HVDC) links for interconnecting asynchronous grids has emerged as a significant trend in modern power systems. To address the issues of limited mutual support capability between regional grids and the declining inertia and primary frequency modulation capability of regional grids with increasing penetration of renewable energy, a coordinated control strategy for HVDC frequency controllers in multi-area asynchronous grids is proposed. Firstly, a frequency control model of multi-area asynchronous grids interconnected by HVDC is constructed, and the dynamic frequency response equations of the system are obtained. Then, considering the types of disturbances in the multi-area system comprehensively, the quantitative analysis of the steady-state frequency deviation(SSFD), and whether the rectifier and inverter sides of each regional grid participate in frequency regulation, the coordinated control strategy for HVDC frequency controllers is obtained based on an exhaustive search algorithm. Finally, the impact of control parameters in the HVDC frequency controller on system frequency stability is analyzed utilizing the state-space model. Considering the results of the stability analysis, an optimization methodology for tuning the droop parameters of the frequency controller is proposed, employing an exhaustive search algorithm. The effectiveness and feasibility of the proposed control strategy and droop parameter tuning method are verified through numerical simulations.

关键词： HVDC Multi-area asynchronous grid Coordinated control strategy Frequency controllers exhaustive search algorithm

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Predicting microRNA modulation in human prostate cancer using a simple String IDentifier (SID1.0)

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JOURNAL OF BIOMEDICAL INFORMATICS 2011年第4期44卷 615-620页

作者： Albertini, Maria C. Olivieri, Fabiola Lazzarini, Raffaella Pilolli, Francesca Galli, Francesco Spada, Giorgio Accorsi, Augusto Rippo, Maria R. Procopio, Antonio D. Univ Urbino Carlo Bo Dipartimento Sci Biomol Sez Biochim & Biol Mol Urbino Italy Univ Politecn Marche Dipartimento Patol Mol & Terapie Innovat Ancona Italy Univ Perugia Dipartimento Med Interna I-06100 Perugia Italy Univ Urbino Carlo Bo Dipartimento Sci Base & Fondamenti Urbino Italy

To make faster and efficient the identification of mRNA targets common to more than one miRNA, and to identify new miRNAs modulated in specific pathways, a computer program identified as SID1.0 (simple String IDentifier) was developed and successfully applied in the identification of deregulated miRNAs in prostate cancer cells. This computationally inexpensive Fortran program is based on the strategy of exhaustive search and specifically designed to screen shared data (target genes, miRNAs and pathways) available from PicTar and DIANA-MicroT 3.0 databases. As far as we know this is the first software designed to filter data retrieved from available miRNA databases. SID1.0 takes advantage of the standard Fortran intrinsic functions for manipulating text strings and requires ASCII input files. In order to demonstrate SID1.0 applicability, some miRNAs expected from the literature to associate with cancerogenesis (miR-125b, miR-148a and miR-141), were randomly identified as main entries for SID1.0 to explore matching sequences of mRNA targets and also to explore KEGG pathways for the presence of ID codes of targeted genes. Besides genes and pathways already described in the literature. SID1.0 has proven to useful for predicting other genes involved in prostate carcinoma. These latter were used to identify new deregulated miRNAs: miR-141, miR-148a, miR-19a and miR-19b. Prediction data were preliminary confirmed by expression analysis of the identified miRNAs in androgen-dependent (LNCaP) and independent (PC3) prostate carcinoma cell lines and in normal prostatic epithelial cells (PrEC). (C) 2011 Elsevier Inc. All rights reserved.

关键词： Computational methods Prostate cancer (CaP) SID1.0 PicTar DIANA-MicroT 3.0 microRNA prediction exhaustive search algorithm Fortran language

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New fast multi-user beam training scheme based on compressed sensing theory for millimetre-wave communication

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IET COMMUNICATIONS 2019年第6期13卷 642-648页

作者： Ding, Yu Su, Li Jin, Depeng Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China Beijing Natl Res Ctr Informat Sci & Technol BNRis Beijing 100084 Peoples R China

Compensating for the considerable propagation loss, millimetre-wave communication systems adopt large antenna arrays and beamforming technologies to obtain high antenna gains. The beamforming training is rather time-consuming especially in multi-user cases. To reduce the training overhead, a new fast multi-user training scheme based on Compressed Sensing theory is proposed. This scheme includes a multi-user training algorithm and a corresponding semi-fixed semi-random codebook design strategy. The base station (BS) simultaneously broadcasts the training pilots to all user equipments (UEs). Then all UEs independently conduct the proposed training algorithm from channel responses. Finally, all UEs send back the training results to the BS. Compared to the exhaustive search algorithm's training overhead xi = KrKt, the cost of the proposed scheme is only O(xi) = log(KrKt), where K-r and K-t denote the number of beam patterns in the receiver and the transmitter. Simulation results show that the proposed scheme achieves excellent performance in high SNR (signal-to-noise ratio) cases with only 3 - 5% performance difference from the theoretical bound. And in contrast with other Compressed Sensing schemes with random codebooks, the proposed scheme reduces the sensitivity to transmission SNR and improves approximately 3 dB performance in low SNR cases.

关键词： radiofrequency interference wireless channels interference suppression antenna arrays radio networks channel estimation error statistics array signal processing multiuser beam compressed sensing theory millimetre-wave communication systems antenna arrays beamforming technologies high antenna gains beamforming training multiuser cases training overhead fast multiuser training scheme multiuser training algorithm base station BS training pilots user equipments UEs training results exhaustive search algorithm Compressed Sensing schemes propagation loss semifixed semirandom codebook design strategy

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A fast search algorithm for the quorumcast routing problem

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INFORMATION PROCESSING LETTERS 1998年第2期66卷 87-92页

作者： Low, CP Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

Multicasting is the transmission of data packets from a source to multiple destinations, known as the multicast group. Quorumcasting, which is a generalization of multicasting, is the sending of these data packets to only a subset of nodes in the multicast group, which we call the quorum group. The quorumcast routing problem is that of finding the least cost tree which spans the source node and a quorum group. This problem is known to be NP-complete. Therefore, exhaustive search algorithms are generally used to find a solution for the problem. In this paper, we introduce the notion of a threshold value and show that how this value can be used to significantly reduce the running time of exhaustive search algorithms for the quorumcast routing problem. (C) 1998 Elsevier Science B.V.

关键词： algorithms quorumcast routing multicast exhaustive search algorithm pruning search space NP-completeness

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On program and file assignment for distributed systems

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COMPUTER SYSTEMS SCIENCE AND ENGINEERING 2004年第1期19卷 39-48页

作者： Liu, GQ Xie, M Dai, YS Poh, KL Natl Univ Singapore Dept Ind & Syst Engn Singapore 119260 Singapore

For distributed computing system, the system reliability which is an important quality and performance metric, depends mainly on the allocation of various resources such as the assignment of executed programs and stored files. This paper first develops a general reliability based optimization model followed by an exhaustive search algorithm and a genetic algorithm to solve the model. The steps of the algorithm are described and numerical examples are used to illustrate the advantages and disadvantages of the two algorithms. The genetic algorithm can generally achieve near-optimal results within a limited amount of computational time, and hence recommended for large distributed systems.

关键词： distributed system reliability file allocation program allocation exhaustive search algorithm genetic algorithm (GA)

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Joint user selection, mode assignment, and power allocation in cognitive radio-assisted D2D networks

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IET COMMUNICATIONS 2018年第10期12卷 1207-1214页

作者： Ahmad, Mushtaq Naeem, Muhammad Iqbal, Muhammad Ejaz, Waleed Anpalagan, Alagan COMSATS Inst Informat Technol Wah Wah Cantonment 47040 Pakistan Ryerson Univ Dept Elect & Comp Engn Toronto ON M5B 2K3 Canada

Device to device (D2D) communications are emerging as an essential part of technological solutions to boost data rates in the next generation networks. Cognitive radio (CR) opportunistically utilises spectrum to boost spectral efficiency. CR-assisted D2D networks will bring the benefits of both D2D as well as CR together in futuristic cellular networks. This study proposes to opportunistically use TV spectrum white spaces. A joint user selection, mode assignment, and power allocation in CR-assisted D2D networks can definitely yield higher data rates. The proposed study maximises data rate together with users' selection fulfilling various users' power, base station's transmit power, quality of service, and interference related thresholds. This problem is mixed integer non-linear programming and considered non-deterministic polynomial time (NP)-complete. Due to the discrete variables in the problem, finding an optimal solution with the help of an exhaustive search algorithm (ESA) becomes very challenging. The problem gets exponentially complex with the increasing number of user pairs. Thus, the need of another method becomes imperative that yields near optimal solution. Mesh adaptive direct search (MADS) algorithm is considered for solution in the CR-assisted D2D network resource management problem. Simulation results using MADS yield near optimal solution confirming the suitability of MADS for CR-assisted D2D networks.

关键词： cellular radio computational complexity nonlinear programming integer programming cognitive radio quality of service search problems radiofrequency interference next generation networks joint user selection mode assignment power allocation data rate spectral efficiency futuristic cellular networks TV spectrum white spaces base station interference related thresholds optimal solution user pairs D2D network resource management problem device-to-device communications next generation networks cognitive radio-assisted D2D networks CR-assisted D2D networks users selection transmit power quality-of-service mixed integer nonlinear programming NP-complete exhaustive search algorithm ESA mesh adaptive direct search algorithm MADS algorithm CR-assisted D2D network resource management problem

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A new optimized algorithm for automating endmember pixel selection in the SEBAL and METRIC models

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REMOTE SENSING OF ENVIRONMENT 2017年 196卷 178-192页

作者： Bhattarai, Nishan Quackenbush, Lindi J. Im, Jungho Shaw, Stephen B. Univ Michigan Sch Nat Resources & Environm Ann Arbor MI 48109 USA SUNY Coll Environm Sci & Forestry Environm Resources Engn Syracuse NY 13210 USA Ulsan Natl Inst Sci & Technol Sch Urban & Environm Engn Ulsan 44919 South Korea

In typical surface energy balance (SEB) models such as surface energy balance for land (SEBAL) and mapping evapotranspiration (ET) at high resolution with internalized calibration (METRIC), calibration of sensible heat flux (H) requires identification of endmember (i.e. hot and cold) pixels. Such pixel selection is typically done manually, which makes it labor intensive to apply SEBAL or METRIC over large spatial areas or long time series. In this paper, we introduce a new automated approach that uses an exhaustive search algorithm (ESA) to identify endmember pixels for use in these models. The fully automated models were applied on 134 near cloud-free Landsat images with each image covering one of four flux measurement sites covering a distinct land cover type in humid Florida or relatively drier Oklahoma. Observed land surface temperatures (T-s) at automatically identified hot and cold pixels were within 0.25% of manually identified pixels (both coefficient of determination, R-2, and Nash-Sutcliffe efficiency, NSE, >= 0.98, and root mean squared error, RMSE, <= 1.31 K). The new fully automated model performed better and demonstrated better consistency than an existing semi-automated method that used a statistical approach to subset coldest and hottest pixels within an image. Daily ET estimates derived from the automated SEBAL and METRIC models were in good agreement with their manual counterparts (e.g., NSE >= 0.94 and RMSE <= 0.35 mm day(-1)). Automated and manual pixel selection resulted in similar estimates of observed ET across all sites. The proposed automated pixel selection approach greatly reduces time demands (e.g. approximately one image per hour vs. hundreds of image per hour) for applying SEBAL and METRIC and allows for their more widespread and frequent use. This automation can also reduce potential bias introduced by an inexperienced operator and extends the domain of the models to new users. (C) 2017 Elsevier Inc. All rights reserved.

关键词： Automation exhaustive search algorithm Endmember pixels SEBAL METRIC

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Energy Harvesting Optimization of Uplink-NOMA System for IoT Networks Based on Channel Capacity Analysis Using the Water Cycle algorithm

IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING

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IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING 2021年第1期5卷 291-307页

作者： Bulut, Ibrahim Serhat Ilhan, Haci Yildiz Tech Univ Dept Elect & Commun Engn TR-34020 Istanbul Turkey

This article presents energy harvesting (EH) in 5G networks for uplink-NOMA systems for Rician and Rayleigh fading channels via optimizing the radio frequency (RF) energy charging period and the data transmission rate for each user. The model aims to maximize the EH system's efficiency depending on the number of users, time-slot, resource blocks, path loss, and base station power (BS). In this work, a simple, efficient, and multi-objective the Water Cycle algorithm (WCA) is presented for calculating transmission rate and EH duration. Furthermore, simulation, performance analysis, and complexity results of WCA are shown by comparing its performance to those of the standard well-known exhaustive search algorithm (ESA), Genetic algorithm (GA), and Particle Swarm Optimization (PSO). According to the optimization results within 6,800,000 possibilities, the WCA provides 11 percent more power allocation for the energy harvesting and more smooth time-sharing per user than the literature.

关键词： Internet of Things NOMA energy harvesting channel capacity Rician fading model water cycle algorithm exhaustive search algorithm

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