APUNTES Y PROPUESTAS PARA LA COOPERACIÓN EN MATERIA DE INTELIGENCIA
Cooperation in the intelligence fi eld, has been a matter of undeniable complexity in all times, notwithstanding sources and methods commitment risks, existing suspicion between allies that may become enemies, and the unavoidable mistrust still existing between intelligence bodies within the country itself, has experienced signi fi cant growth in the last few decades as a result of the emergence of global threats such as terrorism and transnational organized crime among others, and the development of regional and sub regional integration processes, with the subsequent development of common interests. Latin America has witnessed essential changes in this fi eld. From past hemispheric-wide cooperation to fi ght against international communist movements, intelligence cooperation is now focused on public security issues in sub regions, supported basically by different mechanisms, but based on each sub region’s speci fi c needs. Today, UNASUR proposes the possibility and the challenge to develop institutionalized intelligence cooperation mechanisms, both in the fi elds of defense and of public security. This articler explores the history of intelligence cooperation in the region, along with the new opportunities/challenges
Cooperación entre servicios de inteligencia: la dimensión regional
The postmodern world’s characteristics will require increasingly frequent cooperation be-tween intelligence services from different countries, particularly those within the same geopolitical region. The existence of robust and developed formal structures for regional cooperation favors intelligence cooperation, especially when the region’s intelligence culture recognizes these bodies’ role in decision-making. As a typical postmodern entity, the European Union constitutes an ideal set-ting to promote intense and permanent intelligence cooperation. While Latin America is some years behind schedule, it gathers most of the factors that have made the successful European experience possible.
A Short-Term and High-Resolution Distribution System Load Forecasting Approach Using Support Vector Regression With Hybrid Parameters Optimization
This paper proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system. The performance of the proposed approach is compared to some classic methods in later sections of this paper.