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Identify potential circRNA-disease associations through a multi-objective evolutionary algorithm

INFORMATION SCIENCES 2023年第1期647卷

作者： Zhang, Yuchen Lei, Xiujuan Dai, Cai Pan, Yi Wu, Fang-Xiang Shaanxi Normal Univ Sch Comp Sci Xian 710119 Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Fac Comp Sci & Control Engn Shenzhen 518055 Peoples R China Univ Saskatchewan Div Biomed Engn Saskatoon SK S7N5A9 Canada

More and more studies have demonstrated that circRNAs can be used as markers of various diseases due to their inherent stability. Numerous computational methods, especially artificial intelligence approaches, have been applied to the prediction of circRNA-disease associations. However, the objective functions of these prediction methods are usually single and standard. The single objective function hardly reflects the characteristics of the prediction problem, and leads to low prediction accuracy. There has never been a method to design a set of objective functions for the circRNA-disease prediction problem and solve it by using intelligent optimization algorithms. In this paper, a method ICDMOE is proposed to identify circRNA-disease associations via a multiobjective evolutionary algorithm. A solution space is defined and four objective functions are designed based on matrix factorization and modularity of similarity networks. An improved decomposition-based multi-objective evolutionary algorithm (MOEA/D) is also employed to solve these objective functions. In the MOEA/D, an adaptive penalty-based boundary intersection strategy is proposed, which not only ensures convergence, but also guarantees the diversity of solutions in the Pareto front. Finally, the experimental results show that ICDMOE has better performance than pure matrix factorization-based methods, non-adaptive MOEA/D-based methods and other prediction methods. Furthermore, we find that the predicted disease-circRNAs can be confirmed by existing studies, miRNA regulations and expression profiles, etc. These indicate that ICDMOE can provide good candidates for biomedical experiments.

关键词： CircRNA-disease associations Matrix factorization multi-objective functions MOEA/D Adaptive penalty strategy

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Reconfiguration and displacement of DG and EVs in distribution networks using a hybrid GA-SFLA multi-objective optimization algorithm

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FRONTIERS IN ENERGY RESEARCH 2023年 11卷

作者： Ghadi, Yazeed Yasin Kotb, Hossam Aboras, Kareem M. Alqarni, Mohammed Yousef, Amr Dashtdar, Masoud Alanazi, Abdulaziz Al Ain Univ Dept Comp Sci & Software Engn Abu Dhabi U Arab Emirates Alexandria Univ Fac Engn Dept Elect Power & Machines Alexandria Egypt Univ Business & Technol Elect Engn Dept Jeddah Saudi Arabia Alexandria Univ Fac Engn Engn Math Dept Alexandria Egypt Sidi Mohamed Ben Abdullah Univ Fac Sci & Technol Fez Dept Elect Engn Fes Morocco Northern Border Univ Coll Engn Dept Elect Engn Ar Ar Saudi Arabia

A combined algorithm for reconfiguring and placement of energy storage systems, electric vehicles, and distributed generation (DG) in a distribution network is presented in this paper. The impact of this technique on increasing the network's resilience during critical periods is investigated, as well as improvements in the network's technical and economic characteristics. The three objective functions in this regard are the network losses, voltage profile, and running costs, which include the costs of purchasing electrical energy from the upstream network and the devices used, as well as the cost of load shedding. In addition, the impacts of the presence of DG on power flow and the modeling of the problem's objective function are examined. To solve the problem of reconfiguration and placement of a multi-objective distribution feeder, a genetic algorithm (GA) and shuffled frog leaping algorithm (SFLA) hybrid algorithm is used. The proposed GA-SFLA algorithm is used to solve the problem with changes in its structure and its combination in three stages. Finally, the proposed method is implemented on the 33-bus distribution network. The simulation results show that the proposed method has an effective performance in improving the considered objective functions and by establishing a suitable fit between the different objective functions based on the three-dimensional Pareto front. Moreover, it introduced a more optimized architecture with lower loss, lower operating costs, and greater reliability compared to other optimization algorithms.

关键词： multi-objective functions energy storage distributed generation electric vehicles reconfiguration placement GA-SFLA algorithm

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Energy scheduling in a smart energy hub system with hydrogen storage systems and electrical demand management

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JOURNAL OF BUILDING ENGINEERING 2023年 80卷

作者： Javid, Seyed Saeed Mosayebi Derakhshan, Ghasem Hakimi, Seyed mehdi Islamic Azad Univ Dept Elect Engn Damavand Branch Damavand Iran

The energy price uncertainty in energy markets is the main challenge for achieving economic modeling of energy consumption and generation. This paper proposes optimal energy scheduling in a smart energy hub (SEH) under the uncertainty of electricity prices in the day-ahead. The proposed optimization approach is implemented by a two-layer interval approach for minimizing energy generation cost. In first layer optimization, demand side management (DSM) for electrical demand subject to the optimal level of electrical consumption is implemented. In second-layer optimization, the interval approach is used for modeling uncertainty. The energy generation cost is converted to bi-objective functions including average and deviation costs with conflicting nature than each other. Also, the multi-performance of the hydrogen storage system based on electrical and natural gas generation is considered for managing uncertainties in second layer optimization. Since the interval optimization approach is proposed in the second layer, minimizing the average cost and deviation cost are formulated as bi-objective functions by the augmented epsilon-constraint method. In the following, the LINMAP procedure is utilized to achieve maximum compatibility and the best trade-off consequence in the Pareto frontier of the multi-objective functions. Finally, the proposed optimization approach is modeled as a numerical simulation in the case studies to verify obtained results. The participation of the DSM and the hydrogen storage systems leads to minimizing the average and deviation costs by 3.03 % and 3.16 % in comparison with non-participation.

关键词： Smart energy hub (SEH) Demand side management (DSM) Two-layers interval approach Hydrogen storage system multi-objective functions Augmented epsilon-constraint method

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Lane Change Trajectory Planning Based on Quadratic Programming in Rainy Weather

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WORLD ELECTRIC VEHICLE JOURNAL 2023年第9期14卷 252页

作者： Deng, Chengzhi Qian, Yubin Dong, Honglei Xu, Jiejie Wang, Wanqiu Shanghai Univ Engn Sci Sch Mech & Automot Engn Shanghai 201620 Peoples R China Key Lab Prod Defect & Safety State Market Regulat Beijing 100101 Peoples R China

To enhance the safety and stability of lane change maneuvers for autonomous vehicles in adverse weather conditions, this paper proposes a quadratic programming-based trajectory planning algorithm for lane changing in rainy weather. Initially, in order to mitigate the risk of potential collisions on wet and slippery road surfaces, we incorporate the concept of road adhesion coefficients and delayed reaction time to refine the establishment of the minimum safety distance. This augmentation establishes constraints on lane change safety distances and delineates the boundaries of viable lane change domains within inclement weather contexts. Subsequently, adopting a hierarchical trajectory planning framework, we incorporate visibility cost functions and safety distance constraints during dynamic programming sampling to ensure the safety of vehicle operation. Furthermore, the vehicle lane change sideslip phenomenon is considered, and the optimal lane change trajectory is obtained based on the quadratic programming algorithm by introducing the maneuverability objective function. In conclusion, to verify the effectiveness of the algorithm, lateral linear quadratic regulator (LQR) and longitudinal double proportional-integral-derivative (DPID) controllers are designed for trajectory tracking. The results demonstrate the algorithm's capability to produce continuous, stable, and collision-free trajectories. Moreover, the lateral acceleration varies within the range of +/- 1.5 m/s2, the center of mass lateral deflection angle varies within the range of +/- 0.15 degrees, and the yaw rate remains within the +/- 0.1 degrees/s range.

关键词： rainy weather quadratic planning lane change trajectories multi-objective functions

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Systematic Approach To Reduce Uncertainties When Quantitatively Assimilating 4D Seismic and Well Data

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SPE RESERVOIR EVALUATION & ENGINEERING 2020年第1期23卷 13-30页

作者： Almeida, Forlan La Rosa Davolio, Alessandra Schiozer, Denis Jose Univ Estadual Campinas Campinas SP Brazil Univ Estadual Campinas Ctr Petr Studies Campinas SP Brazil Univ Estadual Campinas Sch Mech Engn Campinas SP Brazil

History matching (HM) is a complex process that aims to increase the reliability of reservoir-simulation models. HM is an inverse problem with multiple solutions that call for probabilistic approaches. When observed data are integrated with sampling methods, uncertainty can be reduced by updating the uncertainty distribution of the reservoir properties. This work presents a practical methodology to systematically reduce uncertainties in a multiobjective assisted HM while dealing with multiple scenarios and assimilating well and 4D-seismic (4DS) data quantitatively. The frequency-distribution update goes through an iterative process. The distribution of the current iteration is combined with the histogram generated using the best-matched simulation scenarios from the current iteration to generate the updated distribution. To evaluate the matching quality, multiple local objective functions (LOFs) are independently evaluated, enabling the identification of LOFs that expose the need for reparameterization. This quantitative process was applied in two phases: Phase 1, in which only well data were used to constrain the scenarios, and Phase 2, when 4DS data were added. The methodology was successfully validated against a synthetic benchmark case of medium complexity, with the production-history data generated at a fine scale (reference model). Each iteration increased the number of matched scenarios, demonstrating good convergence. Most of the reservoir properties had uncertainty reduced gradually while avoiding the premature reduction of the uncertainty range (minimizing convergence to an incorrect solution). Local probabilistic perturbations were conducted on the petrophysical realizations in the regions around the wells that manifested LOFs, which hindered the match. The method efficiently achieved multiple matched simulation scenarios, with all (87) LOFs evaluated within the defined tolerance range. The 4DS data were included regionally with an acceptable increase in

关键词： 4D seismic assimilation uncertainty reduction multi-objective functions

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A topology optimization based design of a liquid-cooled heat sink with cylindrical pin fins having varying pitch

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INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER 2021年 172卷 121172-121172页

作者： Lee, Jun Seok Yoon, Sang Youl Kim, Bongjun Lee, Hanchoon Ha, Man Yeong Min, June Kee Pusan Natl Univ Sch Mech Engn 2Busandaehak Ro 63beon Gil Busan 46241 South Korea Pusan Natl Univ Rolls Royce & Pusan Natl Univ Technol Ctr Thermal 2Busandaehak Ro 63beon Gil Busan 46241 South Korea LG Elect H&A R&D Ctr 51Gasan Digital 1-Ro Seoul 08592 South Korea

An improved internal structure of a liquid-cooled heat sink has been proposed numerically and experimentally. The initial motivation is based on the results of thermal and fluid-flow topology optimization, which tends to produce a porous region despite suppression through the numerical scheme. The topology optimization was conducted using a Finite-Volume (FV) based procedure with a simplified sensitivity analysis as well as the globally convergent method of moving asymptotes (GCMMA) algorithm. The Spalart-Allmaras turbulence model was modified to handle the varying solid geometry in the topology optimization. As the result of multi-objective topology optimization showed a tendency towards the porous geometry inside the heat transfer domain, new models for the internal structure were proposed: a multi-layered porous medium with metal foam and varying-pitch cylindrical pin-fin structures. An experimental rig was developed for experimental validation of the proposed idea. The results shows that the varying-pitch cylindrical pin-fin structure inside the heat sink has advantages in heat transfer, pressure drop, and the manufacturability. Details of the numerical procedure and the experimental results are summarized in both quantitative and qualitative aspects. (C) 2021 Elsevier Ltd. All rights reserved.

关键词： Topology optimization Liquid-cooled heat sink Computational fluid dynamics multi-objective functions Porous media Varying-pitch pins

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A mathematical framework for design and optimization of regenerative storage heater

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APPLIED THERMAL ENGINEERING 2018年 135卷 521-529页

作者： Samineni, Nagendra Babu Prabu, T. Yadav, Dasharath Ram Rao, G. Amba Prasad DRDL Hyderabad Telangana India PSG Coll Technol Dept Mech Engn Coimbatore Tamil Nadu India NIT Warangal Dept Mech Engn Warangal Telangana India

The Regenerative Storage Heater (RSH) is employed in Hypersonic Wind Tunnel (HWT) to prevent liquefaction of air during expansion in the high Mach number nozzles. Design of RSH is a multi-variable iterative process depends on the total energy required, the exit temperature of the air and the duration of blowdown. Arriving at the optimal design of RSH is essential as it has a high economic impact. After arriving at the design, evaluation of the performance of RSH for all the possible operating conditions prior to manufacturing is critical. The current research work addresses the challenge by evolving a mathematical framework using multi-objective optimization functions. MATLAB based integrated Graphical User Interface (GUI) has been developed to study the design and analysis simultaneously. This GUI framework defines the inputs, constraints and the parameters of optimal design for the RSH and calculates the optimal size of the RSH. The paper presents the details of the size of the heater for multi hole multi brick configuration in the RSH for a given input conditions of a Mach 5.0 wind tunnel heater case. The current research also presents the details of the temperature profiles of the bed during heating and blowdown cycles. Finally, framework has been used to design the heater for one of the known published data. It is found that the predicted performance of RSH is in good agreement with the published data. This has established the accuracy of the developed framework.

关键词： Regenerative storage heater Mathematical framework Design optimization multi-objective functions Genetic algorithm Heating cycle Blowdown cycle

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The Combination of Evolutionary Algorithm Method for Numerical Association Rule Mining Optimization 10th

The Combination of Evolutionary Algorithm Method for Numeric...

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10th International Conference on Management Science and Engineering Management (ICMSEM)

作者： Tahyudin, Imam Nambo, Hidetaka Kanazawa Univ Grad Sch Nat Sci & Technol Div Elect Engn & Comp Sci Kanazawa Ishikawa Japan

ISBN: (纸本)9789811018374;9789811018367

The numerical problem of association rule mining is an updated issue. Numerous authors propose some methods to solved it. A number of them are using the optimization approach by Particle Swarm Optimization (PSO). The problem is that the PSO trapped in local optima when searched the best particle in every iteration. Many researchers solved this problem by combining with Cauchy distribution because it is tremendous for searching in a large neighborhood. Hence, that combination will be implemented to accomplish the numerical association rule mining problem for some objective functions such as confidence, comprehensibility, interestingness. Based on the result themulti-objective of PSO forNumerical Association Rule Mining Problem with Cauchy Distribution (PARCD) showed the better result than the method of multi-objective Particle Swarm Optimization for Association Rule Mining (MOPAR).

关键词： PSO Cauchy distribution Numerical association rule mining multi-objective functions

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A comparative study of different objective functions to improve the flood forecasting accuracy

A comparative study of different objective functions to impr...

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28th Nordic Hydrological Conference

作者： Jie, Meng-Xuan Chen, Hua Xu, Chong-Yu Zeng, Qiang Tao, Xin-e Wuhan Univ State Key Lab Water Resources & Hydropower Engn S Wuhan 430072 Peoples R China Univ Oslo Dept Geosci Oslo Norway

In the calibration of flood forecasting models, different objective functions and their combinations could lead to different simulation results and affect the flood forecast accuracy. In this paper, the Xinanjiang model was chosen as the flood forecasting model and shuffled complex evolution (SCE-UA) algorithm was used to calibrate the model. The performance of different objective functions and their combinations by using the aggregated distance measure in calibrating flood forecasting models was assessed and compared. And the impact of different thresholds of the peak flow in the objective functions was discussed and assessed. Finally, a projection pursuit method was proposed to composite the four evaluation indexes to assess the performance of the flood forecasting model. The results showed that no single objective function could represent all the characteristics of the shape of the hydrograph simultaneously and significant trade-offs existed among different objective functions. The results of different thresholds of peak flow indicated that larger thresholds of peak flow result in good performance of peak flow at the expense of bad simulation in other aspects of hydrograph. The evaluation results of the projection pursuit method verified that it can be a potential choice to synthesize the performance of the multiple evaluation indexes.

关键词： flood forecasting multi-objective functions projection pursuit single objective function threshold of peak flow

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A new strategy for novel binder discovery in nano and powder injection molding: A metaheuristics-assisted virtual combinatorial materials search

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POWDER TECHNOLOGY 2016年 302卷 187-195页

作者： Lee, Jin-Woong Timilsina, Suman Kim, Gi-Woo Kim, Ji Sik Kyungpook Natl Univ Sch Nano & Adv Mat Engn Gyeongbuk 37224 South Korea Inha Univ Dept Mech Engn Inchon 22212 South Korea

Binder systems can meet various requirements that include excellent fluidity of injection, good strength of a green body, and rapid thermal debinding. This, however, can be a complex process, and novel binders for practical use in nano powder injection molding (NPIM) as well as in powder injection molding (mu PIM) can be hidden in a multi-compositional search space that contains an almost infinite number of combinations of well-known waxes, polymers, and surfactants. To establish novel binder materials systematically from a carefully chosen, 7-dimensional search space of (Carnauba wax (CW) - Emulsifying wax (EW) - Paraffin wax (PW)) - (Polyethylene glycol 20,000 (PEG20000) - Ethylene-vinyl acetate (EVA) - Polypropylene (PP)) - (Stearic acid (SA)) a metaheuristics optimization strategy, such as the elitism-involved non-dominated-sorting genetic algorithm (NSGA-II), was coupled with a virtual combinatorial materials search (VCMS) involving the hybrid evaluation of multi-objective functions on the basis of a semi-theoretical and semi-empirical approach. Although the process started with random compositions, it eventually converged into a series of new quaternary compositions including EW, PW, PEG20000, and SA that show strong potential for practical applications to NPIM and mu PIM. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Metaheuristics Binder Powder injection molding Hybrid evaluation multi-objective functions

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