Hasil untuk "Competition"

A. Dixit, V. Norman

Christopher R. Starr

J. Egge, D. L. Aksnes

Gene M. Grossman, E. Helpman

M. Laver, W. B. Hunt

H. Kokko

Herbert P. Kitschelt, Z. Mansfeldová, R. Markowski et al.

SE McInnes, J. Carlson, Cj Jones et al.

Bo-Juen Chen, Ming-Wei Chang, Chih-Jen Lin

Load forecasting is usually made by constructing models on relative information, such as climate and previous load demand data. In 2001, EUNITE network organized a competition aiming at mid-term load forecasting (predicting daily maximum load of the next 31 days). During the competition we proposed a support vector machine (SVM) model, which was the winning entry, to solve the problem. In this paper, we discuss in detail how SVM, a new learning technique, is successfully applied to load forecasting. In addition, motivated by the competition results and the approaches by other participants, more experiments and deeper analyses are conducted and presented here. Some important conclusions from the results are that temperature (or other types of climate information) might not be useful in such a mid-term load forecasting problem and that the introduction of time-series concept may improve the forecasting.

Allen N. Berger, A. Demirguc-Kunt, R. Levine et al.

J. Huisman, J. Sharples, J. Stroom et al.

Pete Smith, Peter J. Gregory, D. V. van Vuuren et al.

A key challenge for humanity is how a future global population of 9 billion can all be fed healthily and sustainably. Here, we review how competition for land is influenced by other drivers and pressures, examine land-use change over the past 20 years and consider future changes over the next 40 years. Competition for land, in itself, is not a driver affecting food and farming in the future, but is an emergent property of other drivers and pressures. Modelling studies suggest that future policy decisions in the agriculture, forestry, energy and conservation sectors could have profound effects, with different demands for land to supply multiple ecosystem services usually intensifying competition for land in the future. In addition to policies addressing agriculture and food production, further policies addressing the primary drivers of competition for land (population growth, dietary preference, protected areas, forest policy) could have significant impacts in reducing competition for land. Technologies for increasing per-area productivity of agricultural land will also be necessary. Key uncertainties in our projections of competition for land in the future relate predominantly to uncertainties in the drivers and pressures within the scenarios, in the models and data used in the projections and in the policy interventions assumed to affect the drivers and pressures in the future.

Chiun-Chuan Chen, Ting-Yang Hsiao, Shun-Chieh Wang

We investigate traveling wave solutions in the two-species reaction-diffusion Lotka-Volterra competition system under weak competition. For the strict weak competition regime $(b<a<1/c,\,d>0)$, we construct refined upper and lower solutions combined with the Schauder fixed point theorem to establish the existence of traveling waves for all wave speeds $s\geq s^*:=\max\{2,2\sqrt{ad}\}$, and provide verifiable sufficient conditions for the emergence of non-monotone waves. Such conditions for non-monotonic waves have not been explicitly addressed in previous studies. It is interesting to point out that our result for non-monotone waves also hold for the critical speed case $s=s^*$. In addition, in the critical weak competition case $(b<a=1/c,\,d>0)$, we rigorously prove, for the first time, the existence of front-pulse traveling waves.

Geoffrey R. Hosack, Maud El-Hachem, Nicholas J. Beeton

A general system of difference equations is presented for multispecies communities with density dependent population growth and delayed maturity. Interspecific competition, mutualism, predation, commensalism, and amensalism are accommodated. A sufficient condition for the local asymptotic stability of a coexistence equilibrium in this system is then proven. Using this system, the generalisation of the Beverton-Holt and Leslie-Gower models of competition to multispecies systems with possible maturation delays is presented and shown to yield interesting stability properties. The stability of coexistence depends on the relative abundances of the species at the unique interior equilibrium. A sufficient condition for local stability is derived that only requires intraspecific competition to outweigh interspecific competition. The condition does not depend on maturation delays. The derived stability properties are used to develop a novel estimation approach for the coefficients of interspecific competition. This approach finds an optimal configuration given two conjectures. First, coexisting species strive to outcompete competitors. Second, persisting species are more likely in stable systems with strong dampening of perturbations and high ecological resilience. The optimal solution is compared to estimates of niche overlap using an empirical example of malaria mosquito vectors with delayed maturity in the Anopheles gambiae sensu lato species complex.

Xiaowen Chen, Kyle Crocker, Seppe Kuehn et al.

The competition for resources is a defining feature of microbial communities. In many contexts, from soils to host-associated communities, highly diverse microbes are organized into metabolic groups or guilds with similar resource preferences. The resource preferences of individual taxa that give rise to these guilds are critical for understanding fluxes of resources through the community and the structure of diversity in the system. However, inferring the metabolic capabilities of individual taxa, and their competition with other taxa, within a community is challenging and unresolved. Here we address this gap in knowledge by leveraging dynamic measurements of abundances in communities. We show that simple correlations are often misleading in predicting resource competition. We show that spectral methods such as the cross-power spectral density (CPSD) and coherence that account for time-delayed effects are superior metrics for inferring the structure of resource competition in communities. We first demonstrate this fact on synthetic data generated from consumer-resource models with time-dependent resource availability, where taxa are organized into groups or guilds with similar resource preferences. By applying spectral methods to oceanic plankton time-series data, we demonstrate that these methods detect interaction structures among species with similar genomic sequences. Our results indicate that analyzing temporal data across multiple timescales can reveal the underlying structure of resource competition within communities.

Aurelio D. Herraiz, Pablo Salazar-Zarzosa, Cristina Acosta-Muñoz et al.

Land surface phenology is influenced by a complex interplay of various abiotic factors, including climatic, edaphic, and topographic conditions, along with biotic factors such as competition or species composition. It is particularly important to recognize the varied phenological responses of forest species to aridity, which reflect their different adaptations to climate change. Traditional field measurements may not effectively capture these phenological changes across extensive regions. Thus, this study aims to analyse the key phenological indicators of the ten most common Mediterranean forest species using remote sensing data. Specifically, we will investigate how aridity affects these indicators in areas like Southern Spain, where aridity levels are expected to rise, and we will track their changes over time. To achieve this, we processed the maximum monthly Normalized Difference Vegetation Index (NDVI) data from 1994 to 2021, obtained from Landsat 05 and 07 satellites for 2,358 plots of the Spanish National Forest Inventory in Andalucia (Southern Spain). Evergreen species showed the Start Of Season (SOS) in autumn with maximums NDVI in winter (December-February) and the End Of Season (EOS) in late spring with minimums NDVI in summer (June-August), indicating the important effect of precipitation on the physiological response of Mediterranean vegetation. Over the 28-year analysis period, a general positive trend in NDVI (greening) and its associated phenological metrics was observed for most species. However, aridity impacts surface phenology differently among Mediterranean species, notably shortening the growth season of Scots pine and causing significant seasonal phenology shifts in Cork oak, Stone pine, and Aleppo pine. These findings suggest that time-series Landsat data enhances our understanding of forest dynamics and aridity’s effects on vegetation. Remote sensing of forest species’ responses to aridity is crucial for resilience studies and species management in global change scenarios.

Pak Hou Che, Yue Chen

Probabilistic selling is a retail strategy in which consumers purchase products without knowing their exact identities until after purchase, with various applications like gaming and retail; a real-world practice involves retailers may unsealing and reselling goods to meet consumer demand for transparency. This disrupts manufacturers’ strategies designed to adopt the uncertainty for segmentation and pricing. Using a vertically differentiated supply chain model structured as a Stackelberg game framework, this study examines how transparency from retailer unsealing affects profitability, consumer surplus, and market dynamics. Key findings include the following: (1) Unsealing increases retailer profits by aligning pricing with heterogeneous consumer willingness to pay. (2) Introducing a manufacturer’s direct channel reduces unsealing profits via price competition. (3) Unsealing creates conflicts between manufacturers’ design goals and retailers’ profit-driven incentives. By applying a Stackelberg game framework to model unsealing as a downstream transparency decision, this work advances the probabilistic selling literature by offering a structured approach to analyzing how downstream transparency and retailer strategies reshape probabilistic selling and supply chain dynamics. It highlights the need for manufacturers to balance segmentation, pricing, and channel control, offering insights into mitigating conflicts between design intentions and downstream market behaviors.

Rhonda R. Snook

Harrison G. Hong, Marcin T. Kacperczyk

Matthias Függer, Thomas Nowak, Joel Rybicki

One of the key challenges in synthetic biology is devising robust signaling primitives for engineered microbial consortia. In such systems, a fundamental signal amplification problem is the majority consensus problem: given a system with two input species with initial difference of $Δ$ in population sizes, what is the probability that the system reaches a state in which only the initial majority species is present? In this work, we consider a discrete and stochastic version of competitive Lotka--Volterra dynamics, a standard model of microbial community dynamics. We identify new threshold properties for majority consensus under different types of interference competition: - We show that under so-called self-destructive interference competition between the two input species, majority consensus can be reached with high probability if the initial difference satisfies $Δ\in Ω(\log^2 n)$, where $n$ is the initial population size. This gives an exponential improvement compared to the previously known bound of $Ω(\sqrt{n \log n})$ by Cho et al. [Distributed Computing, 2021] given for a special case of the competitive Lotka--Volterra model. In contrast, we show that an initial gap of $Δ\in Ω(\sqrt{\log n})$ is necessary. - On the other hand, we prove that under non-self-destructive interference competition, an initial gap of $Ω(\sqrt{n})$ is necessary to succeed with high probability and that a $Ω(\sqrt{n \log n})$ gap is sufficient. This shows a strong qualitative gap between the performance of self-destructive and non-self-destructive interference competition. Moreover, we show that if in addition the populations exhibit interference competition between the individuals of the same species, then majority consensus cannot always be solved with high probability, no matter what the difference in the initial population counts.