The FDL method makes use of Fibonacci, Dual and Lucas numbers and has shown considerable success in predicting earthquake events locally as well as globally. Predicting the location of the epicenter of an earthquake is one difficult challenge the other being the timing and magnitude. One technique for predicting the onset of earthquakes is the use of cycles, and the discovery of periodicity. Part of this category is the reported FDL method. The basis of the reported FDL method is the creation of FDL future dates based on the onset date of significant earthquakes. The assumption being that each occurred earthquake discontinuity can be thought of as a generating source of FDL time series The connection between past earthquakes and future earthquakes based on FDL numbers has also been reported with sample earthquakes since 1900. Using clustering methods it has been shown that significant earthquakes (<6.5R) can be predicted with very good accuracy window (+-1 day). In this contribution we present an improvement modification to the FDL method, the MFDL method, which performs better than the FDL. We use the FDL numbers to develop possible earthquakes dates but with the important difference that the starting seed date is a trigger planetary aspect prior to the earthquake. Typical planetary aspects are Moon conjunct Sun, Moon opposite Sun, Moon conjunct or opposite North or South Modes. In order to test improvement of the method we used all +8R earthquakes recorded since 1900, (86 earthquakes from USGS data). We have developed the FDL numbers for each of those seeds, and examined the earthquake hit rates (for a window of 3, i.e. +-1 day of target date) and for <6.5R. The successes are counted for each one of the 86 earthquake seeds and we compare the MFDL method with the FDL method. In every case we find improvement when the starting seed date is on the planetary trigger date prior to the earthquake. We observe no improvement only when a planetary trigger coincided with the earthquake date and in this case the FDL method coincides with the MFDL. Based on the MDFL method we present the prediction method capable of predicting global events or localized earthquakes and we will discuss the accuracy of the method in as far as the prediction and location parts of the method. We show example calendar style predictions for global events as well as for the Greek region using planetary alignment seeds.
KEYWORDS: Earthquakes, Stereolithography, Physics, Detection and tracking algorithms, Sun, Mathematical modeling, Global Positioning System, Information theory, Algorithm development, Solar processes
The problem of predicting the occurrence of earthquakes is threefold. On one hand it is necessary to predict the
date and magnitude of an earthquake, and on the other hand the location of the epicenter. In this work after a
brief review of the state of earthquake prediction research, we report on a new leading time precursor for
determining time onset of earthquake occurrence. We report the linking between earthquakes of the past with
those which happen in the future via Fibonacci, Dual and Lucas numbers (FDL) numbers. We demonstrate it here
with two example seed earthquakes at least 100 years old. Using this leading indicator method we can predict
significant earthquake events >6.5R, with good accuracy approximately +- 1 day somewhere in the world. From a
single seed we produce at least 100 trials simultaneously of which 50% are correct to +- 1day. The indicator is
based on Fibonacci, Dual and Lucas numbers (FDL). This result hints that the log periodic FDL numbers are at the
root of the understanding of the earthquake mechanism. The theory is based on the assumption that each
occurred earthquake discontinuity can be thought of as a generating source of FDL time series. (The mechanism
could well be linked to planetary orbits). When future dates are derived from clustering and convergence from
previous strong earthquake dates at an FDL time distance, then we have a high probability for an earthquake to
occur on that date. We set up a real time system which generates FDL time series from each previous significant
earthquake (>7R) and we produce a year to year calendar of high probability earthquake dates. We have tested
this over a number of years with considerable success. We have applied this technique for strong (>7R)
earthquakes across the globe as well as on a restricted region such as the Greek geographic region where the
magnitude is small (>4R-6.5R). In both cases the success of the method is impressive. It is our belief that
supplementing this method with other precursors will enhance significantly the prediction of significant
earthquakes.
KEYWORDS: Networks, General packet radio service, Global system for mobile communications, Network architectures, Telecommunications, Databases, Wireless communications, Intelligence systems, Computer architecture, Internet
The main goal of wireless telecommunication world can be briefly summarized as: “communication anywhere, anytime, any-media and principally at high-data rates.” On the other hand, this goal is in conflict with the co-existence of plenty different current and emerging wireless systems covering almost the whole world, since each one follows its own architecture and is based on its particular bedrocks. This results in a heterogeneous depiction of the hyper-set of wireless communications systems. The scope of this paper is to present a highly innovative and scalable architectural framework, which will allow different wireless systems to be interconnected in a common way, able to achieve resource management optimization, augmentation of network performance and maximum utilization of the networks. It will describe a hierarchical management system covering all GSM, GPRS, UMTS and WLAN networks each one individually, as well as a unified and wide wireless telecommunication system including all later, in order to provide enhanced capacity and quality via the accomplished network interworking. The main idea is to monitor all the resources using distributed monitoring components with intention to feed an additional centralized system with alarms, so that a set of management techniques will be selected and applied where needed. In parallel, the centralized system will be able to combine the aforementioned alarms with business models for the efficient use of the available networks according to the type of user, the type of application as well as the user’s location.
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