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prediction algorithms in matching platforms

ECONOMIC THEORY 2024年第3期78卷 979-1020页

作者： Hamalainen, Saara Petrikaite, Vaiva Univ Helsinki Helsinki Finland Helsinki GSE Helsinki Finland SOE State Registers Vilnius Lithuania

We follow the future trajectory of more targeted wage formation in labor matching platforms, such as freelancing, crowd-sourcing, home-delivery, and ride-hailing, where local job search is coordinated by improving prediction algorithms. A labor matching platform is modelled as a directed search and matching market. We observe that targeted wage setting promotes efficient matching and longer employment spells. However, because a higher employment rate accentuates any disparities between available workers and vacancies, the effects of targeted wage setting on firm competition depend on prevailing market tightness. The impact of targeted wage formation on workers is positive when the vacancy-to-worker ratio is intermediate but turns negative at both extremes. Our results suggest that targeted wage setting may benefit occasional workers while potentially posing drawbacks for full-time platform workers.

关键词： prediction algorithms Matching platforms Efficiency Targeted wages Employment Competitive search equilibrium D82 D83 E24 J64

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prediction algorithms for Train Arrival Time in Urban Rail Transit 20

Prediction Algorithms for Train Arrival Time in Urban Rail T...

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20th IEEE International Conference on Intelligent Transportation Systems (ITSC)

作者： Liu, Yafei Tang, Tao Xun, Jing Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China

ISBN: (纸本)9781538615263

In urban rail transit, the existing methods used for arrival time prediction have low accuracy. A high-precision predictive method for train arrival times can reduce the workload of train drivers by providing the predictive terminal arrival time and satisfy the requirement of headway control model. This paper proposes the predictive algorithms for train arrival times using back-propagation (BP) neural network, wavelet neural network and genetic algorithm. These algorithms include two parts: running time prediction for sections between two stations and dwell time prediction for stations. The real data on train operation are used for training and testing the predictive algorithms. The feasibility of these algorithms is validated. A comparison between these algorithms is given. The results prove that these prediction algorithms for train arrival times achieve high accuracy.

关键词： prediction algorithms Predictive models Training Genetic algorithms Neural networks Rails Conferences

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Eclipse prediction algorithms for Low-Earth-Orbiting Satellites

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2017年第6期53卷 2963-2975页

作者： Jia, Xianghua Xu, Ming Pan, Xiao Mao, Xintao Beihang Univ Sch Astronaut Beijing 100191 Peoples R China Beijing Inst Control Engn Beijing 100094 Peoples R China Beijing Sunwise Space Technol Co Ltd Beijing 100094 Peoples R China

Earth-orbiting satellites experience a partial or full eclipse when they pass through the night side of the Earth. These eclipse events can have significant impacts on the satellite due to the dramatic change of the solar radiation incident. It is therefore essential to propose a high-precision eclipse prediction algorithm or even a space-borne algorithm applied to the satellite to predict the eclipse events autonomously. This paper proposes two eclipse prediction algorithms based on an atypical eclipse condition. The first is the numerical variable-step algorithm whose computation efficiency is superior to the previous fixed-step algorithm due to adopting multiscale step sizes. The other is the autonomous space-borne algorithm, which, based on the analytical solution of the eclipse condition, predicts the penumbra and umbra. Both algorithms have been implemented to the Sun-synchronous orbit and the prediction results are compared with that of the Satellite Tool Kit software. It is indicated that the numerical variable-step algorithm is of high prediction accuracy, whereas the autonomous space-borne algorithm is more suitable for the on-board processor to predict the eclipse due to its reduced computational demands.

关键词： Satellites prediction algorithms Earth Numerical models Algorithm design and analysis Sun Computational modeling

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Segmental Degradation RUL prediction of IGBT Based on Combinatorial prediction algorithms

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IEEE ACCESS 2022年 10卷 127845-127852页

作者： Meng, Linghui Chen, Yiqiang Zhou, Zhenwei Natl Key Lab Sci & Technol Reliabil Phys & Applica Guangzhou 510370 Peoples R China China Elect Prod Reliabil & Environm Testing Res I Guangzhou 510370 Peoples R China

Aiming at the segmentation nonlinear degradation characteristics of IGBT, the traditional single remaining useful lifetime (RUL) method has low accuracy. This paper proposes a method combining gray prediction and particle filter algorithm. The gray prediction model is used for slow degradation trends prediction in the early stage. When the health precusor parameters reach the fault warning line, the improved particle filter algorithm is used for this stage's prediction with the characteristics of fast nonlinear degradation. The comparison analysis result shows that the combinatorial prediction algorithms used in this paper can be better for tracking the degradation trends of IGBT, and the prediction accuracy is higher than either of the two single prediction methods.

关键词： Insulated gate bipolar transistors Predictive models Mathematical models Degradation Data models prediction algorithms Particle filters IGBT power cycling accelerated aging gray prediction particle filter RUL prediction

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Empowering Random Walk Link prediction algorithms in Complex Networks by Adapted Structural Information

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IEEE ACCESS 2024年 12卷 45044-45059页

作者： Dimitriou, Paraskevas Karyotis, Vasileios Ionian Univ Dept Informat Corfu 49100 Greece

In the link prediction problem a relevant algorithm running over a network attempts to determine whether a link between two nodes will exist in the future, given that it is not present at the moment. Most link prediction algorithms take into account the structure of the network on which they are applied and based on this, they attempt to predict the existence or not of future new edges in the network. However, many of them are quite standardized, applying the same concept and parametrization to all networks, thus not always achieving good results in every different network structure. algorithms based on Graph Neural Networks (GNNs) are more adaptive to any network structure but they do not give appreciable results when the only information available is the network structure. In this paper, we propose a new approach to this problem that approximates the structure of a complex network by allowing adjusted weight to this network structure to create additional information, which we can embed into effective algorithms such as local and superposed random walk link prediction. To achieve this goal, we use well-known kernel functions such as Sigmoids, in which we fit their parameters appropriately by a genetic algorithm to achieve the best possible approximation. To demonstrate the effectiveness of our proposed method we have compared our prediction method results based on precision, AUC and AUPR on eleven selected networks of different structures and properties with seven well-known link prediction algorithms and one more utilizing GNNs. In every case, we have improved the results of random walk algorithms and in most cases we achieved better results from all employed benchmark algorithms.

关键词： prediction algorithms Complex networks Indexes Graph neural networks Approximation algorithms Genetic algorithms Measurement link prediction node similarity sigmoid function genetic algorithms algorithm adaptation

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PERFORMANCE OF ADAPTIVE prediction algorithms FOR TRELLIS-CODED QUANTIZATION OF SPEECH

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IEEE TRANSACTIONS ON COMMUNICATIONS 1994年第2-4期42卷 1512-1517页

作者： SRIRAM, P MARCELLIN, MW UNIV ARIZONA DEPT ELECT & COMP ENGN TUCSON AZ 85721 USA

This paper investigates the performance of different adaptive prediction algorithms for use in a low delay, high-quality speech coder at 16 kbit/s. The system to be studied is based on trellis coded quantization (TCQ). In the work presented, we demonstrate that when trellises based on feedback-free convolutional encoding circuits are employed, error propagation in TCQ systems is not a serious problem. Performance comparisons are made using a fixed predictor and four different adaptive predictors. Informal listening tests reveal that the encoded speech is of good communications quality at an error rate of 10(-3). In an ideal channel, a system employing an all-pole least squares lattice predictor with pitch prediction produces reconstructed speech that is nearly indistinguishable from the original.

关键词： prediction algorithms Speech Delay Quantization Convolutional codes Feedback circuits Circuit testing Error analysis Least squares methods Lattices

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Predicting brain network changes in Alzheimer's disease with link prediction algorithms

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MOLECULAR BIOSYSTEMS 2017年第4期13卷 725-735页

作者： Sulaimany, Sadegh Khansari, Mohammad Zarrineh, Peyman Daianu, Madelaine Jahanshad, Neda Thompson, Paul M. Masoudi-Nejad, Ali Univ Tehran Lab Syst Biol & Bioinformat LBB Inst Biochem & Biophys Tehran Iran Univ Tehran Dept New Sci & Technol FNST Tehran Iran Univ Southern Calif Imaging Genet Ctr Inst Neuroimaging & Informat Marina Del Rey CA USA

Link prediction is a promising research area for modeling various types of networks and has mainly focused on predicting missing links. Link prediction methods may be valuable for describing brain connectivity, as it changes in Alzheimer's disease (AD) and its precursor, mild cognitive impairment (MCI). Here, we analyzed 3-tesla whole-brain diffusion-weighted images from 202 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) - 50 healthy controls, 72 with earlyMCI (eMCI) and 38 with lateMCI (lMCI) and 42 AD patients. We introduce a novel approach for Mixed Link prediction (MLP) to test and define the percent of predictability of each heightened stage of dementia from its previous, less impaired stage, in the simplest case. Using well-known link prediction algorithms as the core of MLP, we propose a new approach that predicts stages of cognitive impairment by simultaneously adding and removing links in the brain networks of elderly individuals. We found that the optimal algorithm, called "Adamic and Adar'', had the best fit and most accurately predicted the stages of AD from their previous stage. When compared to the other link prediction algorithms, that mainly only predict the added links, our proposed approach can more inclusively simulate the brain changes during disease by both adding and removing links of the network. Our results are also in line with computational neuroimaging and clinical findings and can be improved for better results.

关键词： stream stage tree type networks T-network Cerebrum CSRP3 gene prediction algorithms Network Alzheimer Disease network links prediction methods AD

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COMPARISON OF ADAPTIVE LINEAR prediction algorithms IN ADPCM

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IEEE TRANSACTIONS ON COMMUNICATIONS 1982年第7期30卷 1775-1785页

作者： HONIG, ML MESSERSCHMITT, DG UNIV CALIF BERKELEY DEPT ELECT ENGN & COMP SCIBERKELEYCA 94720 UNIV CALIF BERKELEY ELECTR RES LABBERKELEYCA 94720

A comparison of adaptive differential pulse code modulation (ADPCM) speech compression systems is made using different recursive adaptive linear prediction algorithms. The particular algorithms considered are 1) a fixed predictor, 2) the adaptive least mean square (LMS) transversal predictor, 3) the LMS (gradient) lattice predictor, 4) the leas squares (LS) lattice predictor, and 5) an LS lattice predictor combined with a third-order pitch inverse filter. The results indicate that for the conditions simulated, the difference in system performance using the different adaptive algorithms is negligible, suggesting that the predictor having the simplest implementation is the best.

关键词： prediction algorithms Lattices Pulse modulation Least squares approximation Pulse compression methods Modulation coding Speech coding Least squares methods Adaptive filters Transversal filters

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Development and validation of prediction algorithms for major depressive episode in the general population

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JOURNAL OF AFFECTIVE DISORDERS 2013年第1期151卷 39-45页

作者： Wang, Jian Li Manuel, Douglas Williams, Jeanne Schmitz, Norbert Gilmour, Heather Patten, Scott MacQueen, Glenda Birney, Arden Univ Calgary Fac Med Dept Psychiat Calgary AB T2N 4Z6 Canada Univ Calgary Fac Med Dept Community Hlth Sci Calgary AB T2N 4Z6 Canada Univ Ottawa Fac Med Dept Clin Epidemiol Ottawa ON K1N 6N5 Canada Univ Calgary Fac Med Dept Community Hlth Sci Calgary AB T2N 1N4 Canada McGill Univ Fac Med Dept Psychiat Montreal PQ H3A 0G4 Canada STAT Canada Hlth Anal Div Ottawa ON K1A 0T6 Canada Univ Calgary Fac Med Dept Psychiat Calgary AB T2N 1N4 Canada

Background: To develop and validate sex specific prediction algorithms for 4-year risk of major depressive episode (MDE) using data from a population based longitudinal cohort. Methods: Household residents from 10 provinces were randomly recruited and interviewed by Statistics Canada. 10,601 participants who were aged 18 years and older and who did not meet the criteria for MDE in the 12 months prior to a baseline interview in 2000/01 were included in algorithm development;data horn 7902 participants who were aged 18 and older and who were free of MDE in 2004/05 were used for validation. Validation was also conducted in sub-populations that are of practice and policy importance. MDE was assessed using the World Health Organization's Composite International Diagnostic Interview (CIDI)-Short Form for Major Depression (CIDI-SFMD). Results: In the training data, the C statistics for algorithms in men was 0.7953 and was 0.7667 for algorithm in women. The algorithms had good predictive power and calibrated well in the development and validation data. Limitations: The data relied on self-report. MDE was assessed with CIDI-SFMD. It was not feasible to validate the algorithms in different populations from different countries. Conclusions: More studies are needed to further validate and refine these algorithms. However, the ability of a small number of easily assessed variables to predict MDE risk indicates that algorithms are a promising strategy for identifying individuals in need of enhanced monitoring and preventive interventions. Ultimately, application of algorithms may lead to increased personalization of treatment, and better clinical outcomes. (C) 2013 The Authors. Published by Elsevier B.V. All rights reserved

关键词： prediction algorithms Major depression Sex-specific Population based

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A LOSS BOUND MODEL FOR ONLINE STOCHASTIC prediction algorithms

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INFORMATION AND COMPUTATION 1995年第1期119卷 39-54页

作者： YAMANISHI, K NEC CORP LTD C&C INFORMAT TECHNOL RES LABSKAWASAKIKANAGAWA 213JAPAN

In this paper, we consider the problem of on-line prediction in which at each time an unlabeled instance is given and then a prediction algorithm outputs a probability distribution over the set of labels rather than {0, 1}-values before it sees the correct label. For this setting, we propose a weighted-average-type on-line stochastic prediction algorithm WA, which can be regarded as a hybrid of the Bayes algorithm and a sequential real-valued parameter estimation method. We derive upper bounds on the instantaneous logarithmic loss and cumulative logarithmic loss for WA in both the example-dependent form and the expected form (the expectation is taken with respect to the fixed target distribution of sequences). Specifically, under some specific parametric assumptions for target rules, we prove that WA is optimal in the sense that the upper bound on the expected cumulative logarithmic loss for WA asymptotically matches Rissanen's coding-theoretic lower bound. Further, we derive an upper bound on the expected cumulative quadratic loss by making use of relationships between the quadratic loss and the logarithmic loss. Throughout the paper, we relate computational learning theory to information theory, most specifically, Rissanen's predictive minimum description length principle, by giving noiseless coding theoretic interpretations to the loss bounds. (C) 1995 Academic Press, Inc.

关键词： Complexity Information Criterion Probability distribution prediction algorithms Information Theory Complexity algorithms Logarithmic Upper bound Minimum description length

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